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Background Data papers have emerged as a powerful instrument for open data publishing, obtaining credit, and establishing priority for datasets generated in scientific experiments. Academic publishing improves data and metadata quality through peer review and increases the impact of datasets by enhancing their visibility, accessibility, and reusability. Objective We aimed to establish a new type of article structure and template for omics studies: the omics data paper. To improve data interoperability and further incentivize researchers to publish well-described datasets, we created a prototype workflow for streamlined import of genomics metadata from the European Nucleotide Archive directly into a data paper manuscript. Methods An omics data paper template was designed by defining key article sections that encourage the description of omics datasets and methodologies. A metadata import workflow, based on REpresentational State Transfer services and Xpath, was prototyped to extract information from the European Nucleotide Archive, ArrayExpress, and BioSamples databases. Findings The template and workflow for automatic import of standard-compliant metadata into an omics data paper manuscript provide a mechanism for enhancing existing metadata through publishing. Conclusion The omics data paper structure and workflow for import of genomics metadata will help to bring genomic and other omics datasets into the spotlight. Promoting enhanced metadata descriptions and enforcing manuscript peer review and data auditing of the underlying datasets brings additional quality to datasets. We hope that streamlined metadata reuse for scholarly publishing encourages authors to create enhanced metadata descriptions in the form of data papers to improve both the quality of their metadata and its findability and accessibility.

t-Testing is a common component of inferential statistics when comparing two means. This paper explains the central limit theorem and the concept of the null hypothesis as well as types of errors. On the practical side, this paper outlines how different t-tests may be performed in Microsoft Excel, for different purposes, both statically as well as dynamically, with Excel's functions.

Plotting data into graphs is a crucial step in data analysis as part of an initial descriptive statistics exercise since it gives the researcher an overview of the shape and nature of the data. Outlier values may also be identified, and these may be incorrect data, or true and important outliers. This paper explains how to access Microsoft Excel's Analysis Toolpak and provides some pointers for the utilisation of the histogram tool within the Toolpak.

Open source software (OSS) is a software product with the source code made public so that anyone can read, analyze, and change or improve the code. The use of this software is under a license, like Apache, GNU, MIT, Mozilla Public, and Eclipse Public License. Open source software development (OSSD) provides high quality assurance through user testing and peer reviews. The quality of these products depends on the size of the product community. This paper discusses the stakeholders of the OSS community, the quality assurance frameworks and models proposed in some studies, some statistics about OSS, the problems that affect the quality of OSSD, and the advantages and disadvantages of OSS compared to closed source software. This allows us to understand how we can achieve and improve the quality assurance and quality control of OSSD.

The following five papers were presented and peer reviewed for the PIA National Congress in Hobart in March 2011. These papers have been included because the editors feel theyare important and should be available to a broad audience. However please note that theydid not go through the academic peer review process for Australian Planner.

Peer reviews and feedback from colleagues give an author other opinions and suggestions to improve a scientific paper. To provide guidance for giving such feedback, this paper presents patterns on how to find, structure, and give feedback on scientific papers. Additionally this paper gives an overview of literature on reviewing scientific papers.

Peer reviews provide a time-honored way to give feedback and evaluate writing, yet few student papers receive this sort of scrutiny. This article examines qualitative and procedural reasons that ha...

The process of developing a publication guide titled “How to write your first academic paper” was presented in this paper. A detailed qualitative approach was followed to extract key elements from transaction and conference papers that appeared in the IEEE Transactions of Information Theory during the past decade. The approach taken was to learn from the experts, in this case IEEE Fellows and distill it into a step-by-step guide, conforming to a set of design principles. The publication guide was implemented at the Faculty of Engineering and many positive results achieved.

This study set out to compare Cochrane reviews and reviews published in paper-based journals. Two assessment tools were used to collect the data, a 23-itemchecklist developed by Sacks and a nine-itemscale developed by Oxman. Cochrane reviews were found to be better at reporting some items and paper-based reviews at reporting others. The overall quality was found to be low. This represents a serious situation because clinicians, health policy makers, and consumers are often told that systematic reviews represent “the best available evidence.” In the period since this study, the Cochrane Collaboration has taken steps to improve the quality of its reviews through, for example, more thorough prepublication refereeing, developments in the training and support offered to reviewers, and improvements in the system for postpublication peer review. In addition, the use of evidence-based criteria (i.e., the QUOROM statement) for reporting systematic reviews may help further to improve their quality.

Clinical trials, systematic reviews and guidelines compare beneficial and non-beneficial outcomes following interventions. Often, however, various studies on a particular topic do not address the same outcomes, making it difficult to draw clinically useful conclusions when a group of studies is looked at as a whole [1]. This problem was recently thrown into sharp focus by a systematic review of interventions for preterm birth prevention, which found that among 103 randomised trials, no fewer than 72 different outcomes were reported [2]. There is a growing recognition among clinical researchers that this variability undermines consistent synthesis of the evidence, and that what is needed is an agreed standardised collection of outcomes – a “core outcomes set” – for all trials in a specific clinical area [1]. Recognising that the current inconsistency is a serious hindrance to progress in our specialty, the editors of over 50 journals related to women’s health have come together to support The CROWN (CoRe Outcomes in WomeN’s health) Initiative (see Figure 1). Figure 1 Aims of The CROWN Initiative. Development of consensus is required around a set of well-defined, relevant and feasible outcomes for all trials concerning particular obstetric and gynaecologic health conditions, such as preterm birth, incontinence, infertility and menstrual problems. With so many subspecialties involved, this is no easy task. Duplication of effort can be avoided by working with the Core Outcome Measures in Effectiveness Trials (COMET) Initiative, which is working towards core data sets for all medical specialties [3]. Production of trustworthy core outcome sets will require engagement with patients, healthcare professionals, researchers, industry and regulators, and the employment of scientifically robust consensus methods [1]. The data for these core outcome sets, once agreed upon, should be collected in trials and reported in publications as standard practice in the future. Journal editors now invite researchers to take the lead in beginning this work. What will we do as editors to support them and their colleagues? First, we are drawing wide attention to The CROWN Initiative by publishing this editorial in the journals listed below. We shall ensure that the global research community, which includes our many reviewers, is aware of the need for core outcome sets. Submissions which describe development of core outcome sets, if deemed acceptable after peer review, will be effectively disseminated. Our collaboration is not for enforcing harmony at the expense of innovation. To quote from the COMET home page (www.comet-initiative.org): “The existence or use of a core outcome set does not imply that outcomes in a particular trial should be restricted to those in the relevant core outcome set. Rather, there is an expectation that the core outcomes will be collected and reported, making it easier for the results of trials to be compared, contrasted and combined as appropriate; while researchers continue to explore other outcomes as well”. We also expect that as new or superior ways of capturing outcomes emerge, core outcome sets will themselves need updating. Producing, disseminating and implementing core outcome sets will ensure that critical and important outcomes with good measurement properties are incorporated and reported. We believe this is the next important step in advancing the usefulness of research, in informing readers, including guideline and policy developers, who are involved in decision-making, and in improving evidence-based practice.

Peer reviewing is a central component in the scientific publishing process. We present the first public dataset of scientific peer reviews available for research purposes (PeerRead v1),1 providing an opportunity to study this important artifact. The dataset consists of 14.7K paper drafts and the corresponding accept/reject decisions in top-tier venues including ACL, NIPS and ICLR. The dataset also includes 10.7K textual peer reviews written by experts for a subset of the papers. We describe the data collection process and report interesting observed phenomena in the peer reviews. We also propose two novel NLP tasks based on this dataset and provide simple baseline models. In the first task, we show that simple models can predict whether a paper is accepted with up to 21% error reduction compared to the majority baseline. In the second task, we predict the numerical scores of review aspects and show that simple models can outperform the mean baseline for aspects with high variance such as ‘originality’ and ‘impact’.

Infections encompass a set of medical conditions of very diverse kinds that can pose a significant risk to health, and even death. As with many other diseases, early diagnosis can help to provide patients with proper care to minimize the damage produced by the disease, or to isolate them to avoid the risk of spread. In this context, computational intelligence can be useful to predict the risk of infection in patients, raising early alarms that can aid medical teams to respond as quick as possible. In this paper, we survey the state of the art on infection prediction using computer science by means of a systematic literature review. The objective is to find papers where computational intelligence is used to predict infections in patients using physiological data as features. We have posed one major research question along with nine specific subquestions. The whole review process is thoroughly described, and eight databases are considered which index most of the literature published in different scholarly formats. A total of 101 relevant documents have been found in the period comprised between 2003 and 2019, and a detailed study of these documents is carried out to classify the works and answer the research questions posed, resulting to our best knowledge in the most comprehensive study of its kind. We conclude that the most widely addressed infection is by far sepsis, followed by Clostridium difficile infection and surgical site infections. Most works use machine learning techniques, from which logistic regression, support vector machines, random forest and naive Bayes are the most common. Some machine learning works provide some ideas on the problems of small data and class imbalance, which can be of interest. The current systematic literature review shows that automatic diagnosis of infectious diseases using computational intelligence is well documented in the medical literature.

This paper studies electrical engineering learners’ preferences for learning methods with various degrees of activity. Less active learning methods such as homework and peer reviews are investigated, as well as a newly introduced very active (constructive) learning method called “slectures,” and some others. The results suggest that graduate students’ perception of the usefulness of the activity increases with its level of activity. For undergraduate students, an increased perception of the usefulness of the activity was observed for lightly active but structured learning methods. Group-based analysis focusing on two types of learners, defined as “instructor-dependent” and “instructor-independent” according to their perception of the usefulness of the classroom lectures, was also performed. The results suggest that instructor-independent learners may benefit more from active learning methods than instructor-dependent learners. For example, instructor-independent undergraduate learners were found to perceive the homework assignment as being more useful than the lectures. Such a preference was not seen in the average group data. In fact, no learning method was found to be perceived as more useful than the lectures, on average. Thus this paper illustrates the pertinence of group-based data analysis.

Purpose The purpose of this paper is to provide an overview of the implementation of a peer support volunteer scheme in a high secure setting and to explore the peer support volunteer’s experiences conducting this role, based predominantly on an assertive rehabilitation ward. Design/methodology/approach This paper has outlined the implementation of the peer support volunteer scheme in a high secure setting and has explored the peer support volunteer’s experiences conducting this role and has explored the views of newly transferred patients who have accessed this scheme. The peer support scheme is based predominantly on an assertive rehabilitation ward. The data have been collected through the completion of detailed questionnaires that have been disseminated to participants through the clinical team. Findings This paper has outlined the implementation of a peer support scheme on an assertive rehabilitation ward within a high secure forensic mental health setting. This paper has explored the role and experiences of a peer support volunteer on an assertive rehabilitation ward and has explored the experience from a service recipient’s perspective also through the completion of questionnaires. This paper has explored the overall benefits of peer support within mental health services to both the volunteer, staff members and to a patient newly admitted to the ward, and has identified the skills that the volunteer is able to develop following contribution in to the peer support scheme. Practical implications This paper has acknowledged that there have been challenges introducing this particular scheme into mental health service teams. Challenges have included establishing appropriate boundaries and dilution of the role due to power imbalances, both between the peer support volunteer and the service recipient, but also between the clinical team that supervises the overall peer support scheme (Christie, 2016). The clinical team within this particular ward have been mindful with regards to the approach that has been utilised and has therefore, included the service users within the overall development of the scheme to encompass the recovery principles, but have continued to review the progression as a team and have taken into consideration all aspects of relational security. Originality/value The paper relating to the implementation of the peer support volunteer scheme in a high secure setting has not been published before and is not under consideration for publication with another journal.

Given the high prevalence and associated cost of chronic pain, it has a significant impact on individuals and society. Improvements in the treatment and management of chronic pain may increase patients’ quality of life and reduce societal costs. In this paper, we evaluate state-of-the-art machine learning approaches in chronic pain research. A literature search was conducted using the PubMed, IEEE Xplore, and the Association of Computing Machinery (ACM) Digital Library databases. Relevant studies were identified by screening titles and abstracts for keywords related to chronic pain and machine learning, followed by analysing full texts. Two hundred and eighty-seven publications were identified in the literature search. In total, fifty-three papers on chronic pain research and machine learning were reviewed. The review showed that while many studies have emphasised machine learning-based classification for the diagnosis of chronic pain, far less attention has been paid to the treatment and management of chronic pain. More research is needed on machine learning approaches to the treatment, rehabilitation, and self-management of chronic pain. As with other chronic conditions, patient involvement and self-management are crucial. In order to achieve this, patients with chronic pain need digital tools that can help them make decisions about their own treatment and care.

The nature of scientific research in mathematical and computational biology allows editors and reviewers to evaluate the findings of a scientific paper. Replication of a research study should be the minimum standard for judging its scientific claims and considering it for publication. This requires changes in the current peer review practice, and a strict adoption of a replication policy similar to those adopted in experimental fields such as organic synthesis. In the future, the culture of replication can be easily adopted by publishing papers through dynamic computational notebooks combining formatted text, equations, computer algebra and computer code.

Active learning and formative assessment techniques are the cutting edge of the modern education. This paper considers peer assessment automation and touches the topic of high actuality in advancing ICT for active learning. The roots of the study are obtained difficulties in adoption of the currently available peer assessment systems to engineering education introductory courses. The main goal of the paper is to collect software requirements and to build a peer assessment system, which may be easily agreed with standard educational routines (e.g. e-mailing) and which is be able to support complex artifacts interchange during a peer assessment session. The software requirements specification (SRS) for such a system has been created as a result of reviewing educational studies, technical reports and academic publications on common peer assessment processes and existing peer assessment systems. We also introduce the open source Mail-based Randomized Double-Blinded Peer-assessment System for Complex Artifacts called PASCA, which is developed according to this SRS and the results of PASCA adoption to an introductory programming course.

Individual research output (IRO) evaluation is a multi-criteria problem often conducted in groups. In practice, it is necessary to concurrently apply both bibliometric measures and peer review when evaluating the IRO. During the peer review process, different evaluators may use different linguistic terms because of individual differences in cognitive styles, and therefore, they may give ratings based on different assessing attitudes. Further, the weights between bibliometric measures and peer subjective judgments are difficult to determine. Motivated by these difficulties, this paper proposes a quantitative context-free grammar judgment description with an embedded assessing attitude. The proposed method quantitatively handles the assessing attitude and increases the flexibility of the linguistic information. Accordingly, this paper develops a multi-criteria group IRO evaluation method with context-free grammar judgments which concurrently considers bibliometric measures and peer review opinions. To overcome the weighting difficulties and achieve the maximum consensus, this paper proposes a distance-based method to determine the evaluators' weights and a weighted averaging operator to compute the criteria weights. After that, a TOPSIS-based aggregation method is applied to aggregate the objective and subjective ratings. A practical case study is then used to test the feasibility of the methodology. Finally, we discuss the effectiveness of the proposed method.

Peer review holds a central place within the scientific communication system. Traditionally, research quality has been assessed by peer review of journal articles, conference proceedings, and books. There is strong support for the peer review process within the academic community, with scholars contributing peer reviews with little formal reward. Reviewing is seen as a contribution to the community as well as an opportunity to polish and refine understanding of the cutting edge of research. This paper discusses the applicability of the peer review process for assessing and ensuring the quality of datasets. Establishing the quality of datasets is a multifaceted task that encompasses many automated and manual processes. Adding research data into the publication and peer review queues will increase the stress on the scientific publishing system, but if done with forethought will also increase the trustworthiness and value of individual datasets, strengthen the findings based on cited datasets, and increase the transparency and traceability of data and publications. This paper discusses issues related to data peer review—in particular, the peer review processes, needs, and challenges related to the following scenarios: 1) data analyzed in traditional scientific articles, 2) data articles published in traditional scientific journals, 3) data submitted to open access data repositories, and 4) datasets published via articles in data journals.

This paper describes an online system that facilitates peer assessment of students' course work and then uses data from individual case writing assignments in introductory financial accounting to empirically examine associations between peer assessment and case writing performance. Through this description and empirical analysis, the paper addresses the following questions: (1) Why use peer assessment? (2) How does online peer assessment work? (3) Is student peer assessment reliable? (4) What do students think of peer assessment? (5) Does student peer assessment contribute to academic performance? Three key findings from this study are that students at the sophomore level were able to generate reasonably reliable feedback for peers, they valued the experiences involved in providing peer feedback, and giving quality feedback had a more significant and enduring impact on students' accounting case analyses than did receiving quality feedback, after controlling for differences in accounting knowledge and case writing skills.

Maintain quality is always an important issue for the software end product. This paper includes how to improve quality of product by detecting possible number of defects potentials. The authors are using an approach called Peer Review for detection of defect potential. In this paper peer review is done using an agile approach. A study has been conducted on three final year projects and includes the detection of maximum number of defect potentials using different peer review techniques. Finally, as a result, total numbers of defects with different review techniques are compared with possible defects.

While the process of peer reviewing journal articles submitted for publication has been extensively investigated, particularly in the biomedical field, the language of peer reviews is relatively unexplored. This paper studies evaluation in an electronic corpus of 228 reviews submitted to the journal English for Specific Purposes (ESP). The research focuses on the things (or entities) evaluated and the adjectives associated with these. Entities and adjectives are categorised and quantified in order to ascertain what things are valued by reviewers and the qualities by which they are judged. The findings suggest that reviewers take on multiple roles, at the same time discouraging the publication of work that fails to meet the required standards and offering encouragement to authors and guiding them towards publication. These findings have implications for authors submitting research papers, those who support authors in this process, and journal editors.

This paper reports on two controlled experiments comparing pair programming with single developers who are assisted by an additional anonymous peer code review phase. The experiments were conducted in the summer semester 2002 and 2003 at the University of Karlsruhe with 38 computer science students. Instead of comparing pair programming to solo programming this study aims at finding a technique by which a single developer produces similar program quality as programmer pairs do but with moderate cost. The study has one major finding concerning the cost of the two development methods. Single developers are as costly as programmer pairs, if both programmer pairs and single developers with an additional review phase are forced to produce programs of similar level of correctness. In conclusion, programmer pairs and single developers become interchangeable in terms of development cost. As this paper reports on the results of small development tasks the comparison could not take into account long time benefits of either technique.

Since the early 1970s, the efficacy of acupuncture for treating clinical conditions has been evaluated in several hundred randomized trials. Results from these trials have been synthesized in systematic reviews. A well-designed systematic review provides the highest level of evidence for establishing the efficacy of a clinical intervention.The present study assesses the source of original literature contributing to Cochrane reviews on acupuncture. Databases searched to retrieve original studies are evaluated. The distribution of controlled trials in acupuncture across different topic areas and journals, the ability of the reviews to provide conclusive results, and the proportion of original studies indexed with MEDLINE are evaluated.Systematic reviews on acupuncture were extracted from the Cochrane Database of Systematic Reviews. The key search term used was "acupuncture." When more than one systematic review was retrieved on the same topic, the most recent review was included. Indexing of individual clinical trials with MEDLINE was searched using the Single Citation Matcher in PubMed.A total of 94 papers were retrieved from the Cochrane database, of which 10 were included in the analysis. The most common subject areas were related to chronic pain. Considerable heterogeneity was observed in the number of databases searched (median 5, range 3-12). A total of 69% (74/108) papers were indexed with PubMed. Only 13% (14/108) of the papers were published in the primary acupuncture journals. Conclusive statements about the efficacy of acupuncture were made in only 2 of the 10 systematic reviews.Considerable methodological diversity exists in the comprehensiveness of database searches for Cochrane systematic reviews on acupuncture. This diversity makes the reviews prone to bias and adds another layer of complexity in interpreting the acupuncture literature.

Many papers in biomedical journals are drafted not by the named authors, but by professional medical writers working under the direction of those authors, usually funded by pharmaceutical companies. Although this practice can improve both the quality and speed of publications, it has attracted controversy as a result of concerns about the inappropriate influence of pharmaceutical companies.To define ethical standards for professional medical writers who prepare papers for publication in medical journals.Guidelines were drafted after a 4-round Delphi consultation among a group of experienced medical writers. The guidelines were then further refined by seeking comments on the draft from a range of interested parties.The guidelines stress the importance of respecting widely recognised authorship criteria, and in particular of ensuring that those listed as named authors have full control of the content of papers. The role of medical writers must be transparent, which normally means a mention in the acknowledgements section, together with a statement about funding. Writers and authors must have access to relevant data while writing papers. Medical writers have professional responsibilities to ensure that the papers they write are scientifically valid and are written in accordance with generally accepted ethical standards.

For more than 20 years, the German Workshop on Medical Image Processing (Bildverarbeitung fur die Medizin, BVM) is held annually and has been established recently as a European conference. In 2010, the workshop was held in Aachen, Germany. Based on a double-blind review process with at least three experts reviewing each manuscript, the best 20 papers have been invited contributing to this special issue. The thirteen submissions received have passed an international peer review process. Finally, eleven papers have been accepted for publication. This includes two invited papers by Scholl et al. and Wismueller.

Message From The Guest Editors Dear Readers It is the great honor for us to edit this special issue of AWERProcedia Information Technology and Computer Science Journal for the selected revised papers presented in the 2nd World Conference on Information Technology (WCIT-2011) held on November 23-27, 2011, at the Queen Elizabeth Elite Suits and Hotel in historical and touristic city of Antalya in Turkey. As the guest editors of this issue, we are glad to see variety of articles focusing on the major topics of the information technology: Algorithms, artificial intelligence, biometrics, biosensors, cellular, automata, computer architecture, computer graphics, computing methodologies, data mining, data warehouse and applications, database systems, decision support systems, digital ecosystems, digital forensics, distance learning, distributed learning environments, e-business, e-commerce, educational applications, educational software, educational technologies, educational computing, e-government, e-marketing, e-publishing, expert systems, fuzzy logic, genetic algorithms & programming, hardware design, human computer interaction, human tracking technologies, industrial applications, information policy making, information retrieval systems, information systems engineering, information technology & agriculture, information technology & arts and design, information technology & commerce, information technology & health, information technology & languages, intelligent and fuzzy information processing, intelligent tutoring systems, interactive learning environments, internet applications, internet security, knowledge engineering, knowledge management, learning management systems, medical informatics, mobile computing, mobile devices, mobile learning, multimedia applications, networked tools, parallel computing, programming languages, remote laboratories/e-lab, social computing, software/distributed systems, software engineering, sport applications, tele-learning, video conferencing, wearable computing, web based language development, web services, wireless and ad-hoc networks and etc. Scholars from all over the world contributed to this issue of the journal. Special thanks are to all the reviewers, the members of the international editorial board, the publisher, and those involved intechnical processes. We would like to thanks all who contributed to in every process to make this issue actualized. A total of 849 abstracts or full papers were submitted for this issue and each paper has been peer reviewed by the reviewers specialized in the related field. At the end of the review process, a total of 274 high quality research papers were selected and accepted for publication. We hope that you will enjoy reading the papers. Best regards Prof. Dr. Hafize Keser Ankara University, Turkey hafizekeser@yahoo.com.tr Sezer Kanbul, M.Sc. Near East University, North Cyprus sezerkanbul@yahoo.com

Having now accumulated several years of experience as an editor, I have encountered many of the common errors that authors make. As an author, I made them, too, and sometimes still do. Writing for publication in a research or technical field is, after all, a learned skill, honed with practice but rarely perfect. One area that I have noticed where few authors demonstrate well-developed skills is in communicating adequately when describing their response to peer reviews. My observation is not limited to novice authors, who we might expect to be less effective due to their limited experience in performing the skill. Even established authors, who generally submit papers that are better and more clearly written, contain more essential-and less inessential-information, and adhere more closely to publication and APA guidelines, are no less immune to communicating wanting descriptions of their revisions. I may seem picky about this point in particular because the quality of an author's description of how they responded to reviewer comments definitely affects the amount of time and effort I must devote to understanding and evaluating the adequacy of the revisions that the author has made. I'm a busy person, too, who'd like to devote such time to my own publications. But, I think it goes further than that. I have found that the quality of the communication about the revisions often reflects the quality-that is the depth, thoroughness, precision, accuracy, and the like-of the actual revisions. In executing my duty to uphold standards of scientific integrity at the gateway of dissemination, I sometimes wonder if the effort I am putting into evaluating a paper exceeds the investment of the author in writing it. Although I am generally enthusiastic about supporting the work of nurse scientists, especially emerging ones, when I find myself having to dig deeply to figure out what's what, I begin doubting whether the paper will merit eventual publication, even if it is promising. I am reminded of the Tough Love principle: When you are working harder than your progeny to correct their problems, you are working too hard. Perhaps it is an author's eagerness to complete the revisions and get them back to an editor that contributes to a limited description of what was done. Might the author think differently about the task if recognizing that the description is what the editor will actually read first? So, what am I looking for in a good response to reviewer comments? Here are some pointers on what I-and I suspect most editors-want to see. Then, in regard to each pointer, I share my methods as an author for constructing a response. First, I want to see that you understood all that the reviewer is telling you. In my own work, I think of working with reviewer comments similarly to doing a content analysis. I parse them; organize the parcels of information according to relevant segments of the paper or parts of a research report, often in a spreadsheet if they are extensive. Next, I group similar comments and look for congruence or discrepancies across them. Then, I condense and summarize the content of the reviews to consolidate my own understanding of the major messages contained therein and the relative weight or importance of each. If I am having difficulty in arriving at a coherent understanding, I will involve co-authors, trusted advisors, or consultants at this point. This approach works equally well for responding to grant reviews, I might add. Second, I want to know your reaction to each message. Do you agree, disagree, partially agree? And, why! As an author, here is where I start by thinking about the messages, one by one, usually in order of importance, although I might choose to resolve the easy ones first. I may assign the various messages a priority in one column of the spreadsheet. I evaluate the quality or validity of the comments, asking: "Is this substantive? Did the reviewer grasp my message? Did I convey my idea clearly? …

Peer-review systems such as SWoRD lack intelligence for detecting and responding to problems with students’ reviewing performance. While prior work has demonstrated the feasibility of automatically identifying desirable feedback features in free-text reviews of student papers, similar methods have not yet been developed for feedback regarding argument diagrams. One desirable feedback feature is problem localization, which has been shown to positively correlate with feedback implementation in both student papers and argument diagrams. In this paper we demonstrate that features previously developed for identifying localization in paper reviews do not work well when applied to peer reviews of argument diagrams. We develop a novel algorithm tailored for reviews of argument diagrams, and demonstrate significant performance improvements in identifying problem localization in an experimental evaluation.

This paper deals with managing the peer review process with an electronic management system (EMS). Our approach uses a WWW-based interface to an Oracle database. We describe different aspects of the EMS, namely the peer review process, report generation, and security. An experimental peer review system was developed for the Fourth International World Wide Web (WWW) Conference, which provided a model to automate the underlying processes that had been driven primarily by pen and paper. This system uses the very technology that the International WWW Conference Committee (IW3C2) promotes, so it is fitting that the conference be automated with a WWW-based system. The experimental system has evolved with the help of many suggestions to provide better support for the WWW5 conference as well. This paper discusses the first experimental system, some lessons learned, and the second more evolved system for the WWW5 conference with emphasis on the latter.

SUMMARY This paper describes a two‐year observation of peer review among first year undergraduates at Loughborough University of Technology. Peer review focuses on the learning benefits of small group work and the development of critical skills among students as a precursor to peer assessment of tutorial contributions. The paper outlines the methodology, design and pitfalls of the peer review process and offers tentative interpretations of some peer generated marks. The findings of the two‐year study generally support the available literature regarding reliability of peer generated marks and underlines the importance of ‘ownership'and understanding of review criteria. The exercise has provided the necessary experience and detailed feedback to harness its more positive lessons for the launch of peer assessment in the future.

Peer review expert selection is an important link of fund project review; it can not only improve the matching accuracy of domain experts and projects, but also improve the appraisal quality in fund project review. This paper mainly studies the peer review expert selection method in fund project review. With the actual experience of fund project management, based on the author's knowledge set theory, paper analyzes deeply knowledge set representation of expert knowledge, improves the similarity calculation of expert and project knowledge, builds the peer review expert selection method, and gives the actual example.

In this paper we present a study where a peer reviewing system targeted for conference paper evaluation has been used for enhancing the learning of programming though peer review. For peer reviewing purposes two open source systems were evaluated and MyReview was selected for evaluation. The peer review system was used in one programming focused course and the benefits of peer reviewing were analyzed from the reviewer and reviewee point of view. The results show that a peer review system targeted for conference paper evaluations is applicable for reviewing programs although the system should be much simpler. Students appreciated the documented comments from other students but were more interested in lecturer or other expert opinion.

Malaria is a leading cause of death in Nigeria and remains a public health concern because of the increasing resistance of the disease to antimalarial drugs. Pregnant women and children under five years of age are the most vulnerable. Efforts to eradicate malaria is often frustrated due to some various sociodemographic factors and medical factors. One of the vital therapeutic factors is misdiagnosis. Hence, the paper applied different data mining models to diagnose malaria using fifteen symptoms of patients that attended a hospital in Nigeria. The data were obtained from a peer reviewed data article that comprises 337 subjects at Federal Polytechnic Ilaro Medical Centre, Ogun State. The independent variables are 15 symptoms, age, and sex, while the target or dependent is the outcome. The outcome is the result of the diagnosis, which is positive for negative for malaria. Eight machine learning tools were applied to the data on the Orange Software platform. Weak non-significant correlations were obtained between the 15 symptoms and the outcome, and hence no pattern was observed. However, the application of data mining tools revealed a hidden pattern that correctly predicted the outcome using the subjects' symptoms, age, and sex. 6 out of the 8 machine learning models were adjudged to perform well using different performance metrics. The Adaptive boosting model gave a percent 100% precision in the classification, and logistic regression was the least. Furthermore, a percent performance of Adaboost implies that the model correctly predicted all the 221 true negatives and 116 true positives with a misclassification (misdiagnosis) of zero. Classify using only the 15 symptoms reduced the predictive accuracy of the 6 models. Nevertheless, Adaboost performance was the best with a classification accuracy of 98.2%, precision of 96.6%, and an error rate of just 1.8%. Again, logistic regression performance was the least. The present work has presented a strong relationship between age and sex and the outcome. Adaboost model can be used to design decision support systems or rapid diagnostic tools that utilise the internet or mobile devices as platforms in the diagnosis of malaria. The application of the present work as potentials in reduction of misdiagnosis incidences, reducing the mortality due to malaria and improving the overall public health of people residing in malaria endemic areas.

The review cycle for papers takes way too long in many disciplines. The problem is that while authors want to have their own papers reviewed fast, that are often unwilling to review the papers of others in a timely manner. This paper explores what would be required to incentivize fast reviews using a public reputation/scoring system that exploits the fact that the referees are drawn from the same pool as paper authors. The challenge in maintaining a public reputation system is to ensure that the identity of referees remain as anonymous as possible. A model is proposed in this work, wherein authors have an incentive to commit to reviewing papers and are rewarded for meeting this commitment in a manner that prioritizes their own papers for reviews. This ensures stability (bounded reviewing delays) for all fair contributors while freeloaders face a potentially unstable system. A naive implementation of the scoring system, however, leaks information that would allow authors to infer the likely identities of their referees. A distortion to the observed public score process is then studied, which is shown to enhance anonymity while preserving the incentives for timely refereeing.

This paper proposes that experience knowledge would be beneficial for iterative software development. In this paper, experience knowledge- based artifacts have been linked to Extreme Programming via peer reviews. Experience knowledge can be defined as human experiences documented with the object of exploiting them in the organization. Extreme Programming has been selected to represent iterative software development processes. Systematically gathering experiences would support building evidence for improving and teaching iterative software development processes. This paper presents one possible solution as to how to put experience knowledge in practice in the context of iterative software development processes. It also reports results from projects where experience knowledge has been studied. The main findings of this paper are two ways in which experience knowledge- based artifacts can be used with iterative software development, and that peer reviews are a good way to collect and treat experience knowledge-based artifacts.

Autonomous underwater vehicles (AUVs) are efficient sensor-carrying platforms for mapping and monitoring undersea ice. However, under-ice operations impose demanding requirements to the system, as it must deal with uncertain and unstructured environments, harsh environmental conditions, and reduced capabilities of the navigational sensors. This paper proposes a Bayesian approach to supervisory risk control, with the objective of providing risk management capabilities to the control system. First, an altitude guidance law for following a contour of an ice surface via pitch control using measurements from a Doppler velocity log (DVL) is proposed. Furthermore, a Bayesian network (BN) for probabilistic reasoning over the current state of risk during the operation is developed. This is then extended to a decision network (DN) for autonomously adapting the behavior of the AUV in order to maximize the mission utility, subject to a constraint on the predicted risk from the risk model. The vehicle is thus able to autonomously adapt its behavior in response to its current belief about the risk. The goal of this work is to improve the AUV performance and likelihood of mission success. Results from a simulation study are presented in order to demonstrate the performance of the proposed method.

A “digital manuscript” is a manuscript created and transfenred in an electronic format rather than in a paper medium. A digital manuscript encapsulates in a single integrated electronic document all components of a paper-based manuscript (i.e., text, tables, figures, and images) and other components not possible with hard copy, such as digital video and audio. The potential advantages of the digital manuscript are manifold and include (1) facilitation of collaboration among authors; (2) faster and more convenient peer review; (3) less use of consumable materials; (4) less expensive preparation and improved quality of illustrations and figunes; (5) more powerful methods, such as multimedia, to convey information to the reader; (6) elimination of nedundant steps in the publication process; (7) rapid access to published material; and (8) more powerful methods to catalogue and digitally search published literature. There is little doubt that traditional paper-based methods of conveying and archiving information will be increasingly supplanted by electronic methods. However, for these advantages to be realized, several components of our electronic infrastructure need to be upgraded, standardized, and made widely available for authors, reviewers, editors, and publishers. This commentary focuses on the potential advantages, disadvantages, and technological issues of the digital manuscript.

I wish to extend my deep appreciation to all those who have so generously volunteered their time and talents during 2015 to the peer review and publication of the IEEE Transactions on Broadcasting . Special thanks go to our BTS Publications Chair and Associate Editors who have shared their valuable time and broadcast engineering expertise in managing a steadily increasing flow of papers and evaluating manuscripts through the peer review process.

Community acquired pneumonia (CAP) is an acute respiratory disease with a high mortality rate. CAP management follows clinical and radiological diagnosis, severity evaluation and standardised treatment protocols. Although established in practice, protocols are labour intensive, time-critical and can be error prone, as their effectiveness depends on clinical expertise. Thus, an approach for capturing clinical expertise in a more analytical way is desirable both in terms of cost, expediency, and patient outcome. This paper presents a systematic literature review of Machine Learning (ML) applied to CAP. A search of three scholarly international databases revealed 23 relevant peer reviewed studies, that were categorised and evaluated relative to clinical output. Results show interest in the application of ML to CAP, particularly in image processing for diagnosis, and an opportunity for further investigation in the application of ML; both for patient outcome prediction and treatment allocation. We conclude our review by identifying potential areas for future research in applying ML to improve CAP management. This research was co-funded by the NIHR Leicester Biomedical Research Centre and the University of Leicester.

We present an annotation approach to capturing emotional and cognitive empathy in student-written peer reviews on business models in German. We propose an annotation scheme that allows us to model emotional and cognitive empathy scores based on three types of review components. Also, we conducted an annotation study with three annotators based on 92 student essays to evaluate our annotation scheme. The obtained inter-rater agreement of {\alpha}=0.79 for the components and the multi-{\pi}=0.41 for the empathy scores indicate that the proposed annotation scheme successfully guides annotators to a substantial to moderate agreement. Moreover, we trained predictive models to detect the annotated empathy structures and embedded them in an adaptive writing support system for students to receive individual empathy feedback independent of an instructor, time, and location. We evaluated our tool in a peer learning exercise with 58 students and found promising results for perceived empathy skill learning, perceived feedback accuracy, and intention to use. Finally, we present our freely available corpus of 500 empathy-annotated, student-written peer reviews on business models and our annotation guidelines to encourage future research on the design and development of empathy support systems., Comment: to be published in The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)

Background The Distress Thermometer is the most widely used rapid screening tool for assessing psychological distress in people affected by cancer. Use of such tools to assess patients emotional and physical needs is a requirement of the NICE guidelines for supportive and palliative care. Aims To explore the assumption that the Distress Thermometer improves clinicians9 understanding of the concerns of people affected by cancer. Two questions were posed: 1. In what settings and with what populations has the Distress Thermometer been used? 2. What evidence concerning validity exists for this tool and what is the strength of evidence? Methods A systematic review using a framework for mixed evidence (Hawker et al . 2005) across 11 databases. Inclusion criteria: Question 1: papers documenting use of the Distress Thermometer with people affected by cancer, in English, published in peer reviewed journals after 1st January 1998. Question 2: papers (ie, subset of the main search) reporting assessments of the validity of the Distress Thermometer. Results The authors identified 86 papers reporting use of the Distress Thermometer. Populations included: patients with a specific tumour site, older people, children, adult survivors of childhood cancer, caregivers, relatives/partners of cancer patients and people with new diagnoses and advanced disease. Of 86 papers, 33 examined the validity of the Distress Thermometer, with most comparing the tool with other measures, most commonly the Hospital Anxiety and Depression scale. Conclusions Although the Distress Thermometer is widely used in cancer supportive and palliative care across a diverse range of settings and in many populations, there is little evidence to support its validity and little is known about what the tool actually measures. Future research must compare the Distress Thermometer with qualitative interviews and the true ‘gold standard’ of asking patients how distressed they feel and what concerns are contributing to that distress.

Zlto(zlah-toh) is a project to provide secure validation of credentials for young people. Many African youth find it difficult to obtain jobs because of a lack of formal qualification, but they have a breath of informal skills. In this paper we will describe how we implement the Zlto system to provide proof of skills completed through a peer-to-peer evaluation mechanism and stored using blockchain. Since its first deployment in 2016, Zlto has processed over 1 million transactions. We present simulation and analysis of the reputation protocol used to verify work, and further evaluate the peer review process using a think a loud focus group method with a group of peer reviewers in order to improve the system.

The strength and vitality of publications in our profession and pharmaceutical science disciplines are centered on the premise of a high-quality manuscript peer review process. Peer review is the essential element in promoting quality and excellence in the papers published in our scientific, educational, and professional journals. Peer review provides authors with the opportunity to improve the quality and clarity of their manuscripts. It also guides the journal's editorial staff in making publication decisions and identifying substandard manuscripts that should not be published. Individuals who participate in the peer review process provide a valuable service to their colleagues and the journal's editorial staff members by improving the literature in their discipline. Serving as a manuscript peer reviewer is an important, critical professional activity and responsibility. New reviewers may not have been mentored by senior faculty members or gained experience by editing their colleagues' papers. In fact, when presented with the first opportunity to review a manuscript, most reviewers have neither received any instruction nor guidance in how to conduct a manuscript review nor is the process something that is easily mastered.1 The goal of this communication is to provide suggestions how to improve the quality of the peer review process and assist new reviewers with insights and guidelines for conducting a comprehensive, impartial, and fair review. Useful alternative resources for the new reviewer include the works of Provenzale and Stanley1 and Scheife and Cramer.2

Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly develop behavioral risk factors in humans. Behavioral risk factors such as unhealthy habits, improper diet, and physical inactivity lead to physiological risks, and &ldquo, obesity/overweight&rdquo, is one of the consequences. &ldquo, Obesity and overweight&rdquo, are one of the major lifestyle diseases that leads to other health conditions, such as cardiovascular diseases (CVDs), chronic obstructive pulmonary disease (COPD), cancer, diabetes type II, hypertension, and depression. It is not restricted within the age and socio-economic background of human beings. The &ldquo, World Health Organization&rdquo, (WHO) has anticipated that 30% of global death will be caused by lifestyle diseases by 2030 and it can be prevented with the appropriate identification of associated risk factors and behavioral intervention plans. Health behavior change should be given priority to avoid life-threatening damages. The primary purpose of this study is not to present a risk prediction model but to provide a review of various machine learning (ML) methods and their execution using available sample health data in a public repository related to lifestyle diseases, such as obesity, CVDs, and diabetes type II. In this study, we targeted people, both male and female, in the age group of &gt, 20 and &lt, 60, excluding pregnancy and genetic factors. This paper qualifies as a tutorial article on how to use different ML methods to identify potential risk factors of obesity/overweight. Although institutions such as &ldquo, Center for Disease Control and Prevention (CDC)&rdquo, and &ldquo, National Institute for Clinical Excellence (NICE)&rdquo, guidelines work to understand the cause and consequences of overweight/obesity, we aimed to utilize the potential of data science to assess the correlated risk factors of obesity/overweight after analyzing the existing datasets available in &ldquo, Kaggle&rdquo, University of California, Irvine (UCI) database&rdquo, and to check how the potential risk factors are changing with the change in body-energy imbalance with data-visualization techniques and regression analysis. Analyzing existing obesity/overweight related data using machine learning algorithms did not produce any brand-new risk factors, but it helped us to understand: (a) how are identified risk factors related to weight change and how do we visualize it? (b) what will be the nature of the data (potential monitorable risk factors) to be collected over time to develop our intended eCoach system for the promotion of a healthy lifestyle targeting &ldquo, obesity and overweight&rdquo, as a study case in the future? (c) why have we used the existing &ldquo, UCI&rdquo, datasets for our preliminary study? (d) which classification and regression models are performing better with a corresponding limited volume of the dataset following performance metrics?

Peer assessment is widely used in educational settings as an alternative evaluation approach. It brings various benefits to the students, increasing engagement and interactivity and fostering critical thinking and reflection. Several platforms for managing the peer review process have been proposed in the literature, but most of them are confined to a particular domain or course and have various limitations related to reliability, reviewer allocation, reputation and training of reviewers or instructor support. In an attempt to address these challenges, we propose an innovative general-purpose peer assessment platform, called LearnEval. In this paper we focus on the student module part of the system, describing its functionalities, pedagogical rationale and implementation details.

Prior research and anecdotal evidence suggest that the market success of experience goods (i.e. motion pictures) can be empirically connected to professional and peer reviews of those experience goods. In this paper, this argument is tested by examining the way in which reviews determine the success of video games. A number of analysis strategies are used to show that professional critics’ reviews of games can influence sales of games. The amount of advertising is also an influential factor.

The megajournal is a new form of an academic open-access journal that is peer reviewed for scientific and methodological soundness. Thus, the perceived importance is not assessed, leaving it to the readers to decide whether an article is of interest and importance to them. After the highly successful launch of the PLOS ONE megajournal, other publishers followed this path. The current paper undertakes a review of the articles published internationally on the megajournal criteria defining its concept. It also traces how the new type of scientific publication has been developing and expanding since the PLoS ONE launch in 2006.

The current, and welcome, focus on standardization of techniques and transparency of reporting in the biomedical, peer-reviewed literature is commendable. However, that focus has been intermittent as well as lacklustre and so failed to tackle the alarming lack of reliability and reproducibly of biomedical research. Authors have access to numerous recommendations, ranging from simple standards dealing with technical issues to those regulating clinical trials, suggesting that improved reporting guidelines are not the solution. The elemental solution is for editors to require meticulous implementation of their journals’ instructions for authors and reviewers and stipulate that no paper is published without a transparent, complete and accurate materials and methods section.