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93 results for “peer review”
test upload to demonstrate private sharing for peer review
<p>disclose data for double-blind review and make it archived open data upon acceptance</p>
Blockchain and Its Application in the Peer Review of Scientific Papers: A Systematic Review
<p><span>Blockchain is a distributed ledger technology that ensures the security and transparency of data, guaranteeing that it cannot be altered. Its application in the peer review of scientific papers can contribute to improving the integrity, transparency, and efficiency of the process, mitigating issues of manipulation and fraud. This work analyzes the contributions of various research studies that address the use of blockchain technology in peer review. The study is a systematic literature review (SLR) in which the PRISMA methodology was applied. Fifty primary studies were identified through searches in databases such as Scopus, Science Direct, IEEE Xplore, and ACM. The analyzed research reveals innovative approaches, such as decentralized solutions, smart contracts, and token economy, to address challenges like biases, transparency, and speed in the review process. It is concluded that this technology can enhance the transparency and efficiency of peer review, and has the potential not only to overcome current limitations in peer review but also to redefine the structure and culture of scientific research.</span></p>
Figure 1 from: Troncoso-Palacios J, Ruiz De Gamboa M, Langstroth R, Ortiz JC, Labra A (2019) Without a body of evidence and peer review, taxonomic changes in Liolaemidae and Tropiduridae (Squamata) must be rejected. ZooKeys 813: 39-54. https://doi.org/10.3897/zookeys.813.29164
Figure 1 Outline of the non-standard presentation of the three species proposed by Demangel Miranda (2016a).
Dataset for "Using Peer Review to Evaluate the Societal Relevance of Humanities Research"
<p>Data for the study on using peer review for evaluating the societal relevance of humanities research. In addition, the study exploratorily uses peer review to measure the societal relevance of humanities research.</p> <p>The raw data for studies 1 and 2 was published earlier as a previous version of this dataset. This updated version again includes the raw data of studies 1 and 2, but now also the raw data of study 3 as well as the combined, processed data of all three studies. This is the dataset that was used for the analyses described in the paper that we wrote about this study.</p>
Exploring transparency in peer review: A study describing the content and tone of reviewers' confidential comments to editors
<p>This data set was created to conduct - Exploring transparency in peer review: A study describing the content and tone of reviewers’ confidential comments to editors. Prior to data collection, the study received ethical approval the Dutch Association for Medical Education Ethics Review Board. A preprint of the study is available on <a href="https://www.biorxiv.org/content/10.1101/2021.07.28.454037v1.full">bioRxiv</a>. </p> <p>Purpose: Recent calls to improve transparency in peer review have prompted examination of many aspects of the peer review process. Confidential comments to editors are a common component of many peer review systems that have clear implications for transparency, yet how reviewers use this component has escaped scrutiny in the published literature. Our study explores 1) how reviewers use the confidential comments section and 2) the alignment between comments to the editor and comments to authors with respect to content and tone. </p> <p>Methods: Our dataset consisted of 358 reviews of 168 manuscripts submitted between January 1, 2019 and August 24, 2020 to a top tier health professions education journal with a single blind review process. We first examined each review to determine whether the reviewer entered comments to the editor. Then, for the subset of reviews with comments, we used procedures consistent with conventional and directed qualitative content analysis to develop a coding scheme and code comments for content, tone, and section of the manuscript. For reviews in which the reviewer recommended reject, we coded for alignment between reviewers’ comments to the editor and to authors. We report descriptive statistics.</p> <p>Results: Nearly half of the reviews contained comments to the editor (49%). Most of these comments (n=176) summarized the reviewers’ impression of the article (85%), which could include explicit reference to their recommended decision (44%) or comments on suitability for the journal (10%). The majority of comments addressed the quality of the argument (56%) or research design, methods, or data (51%). The tone of comments to the editor tended to be critical (40%) or constructive (34%). For the 48 reviews recommending reject, the majority of comments to editor contained content that also appeared in comments to the authors (65%); additional content tended to be irrelevant to the manuscript. Tone frequently aligned (85%).</p> <p> </p> <p>Conclusion: Our findings indicate variability in how reviewers use the confidential comments to editor section in online peer review systems, though generally the way they use them suggests integrity and transparency to authors.</p>
Test upload to demonstrate private sharing for peer review
<p>This is a dummy file to demonstrate how Zenodo supports double blind peer review</p>
Data from: Trade-offs in Coordination Strategies for Networked Jazz Performances (anonymized for peer review)
<p>This dataset is associated with the paper “Trade-offs in Coordination Strategies for Networked Jazz Performances” and includes recordings of improvisations by jazz duos over a network.</p> <p><strong>Introduction:</strong></p> <p>This dataset includes data from approximately four hours of live, improvised musical duo performances over a simulated network environment collected in LOCATION REMOVED FOR PEER REVIEW. Data includes audio and video recordings of 130 individual performances, biometric data, and subjective evaluations and comments from the musicians. The primary aim of the project was to collect data via a novel performance capture and manipulation system for use in the empirical modelling of ensemble coordination strategies during networked music-making. This analysis is reported in ANONYMIZED FOR PEER REVIEW. Please refer to this publication for full details on the data collection procedure.</p> <p>The ten musicians shown in these recordings were recruited for their expertise in jazz improvisation. They were grouped into five duos consisting each of one pianist and drummer, with no musician performing in more than one duo. Participants were instructed to improvise together over a standard twelve-bar blues musical structure, but following a formula which required them to provide a clear and unambiguous pulse of continuous quarter notes. Varying amounts of network latency and jitter were simulated for each performance, consisting respectively of the minimum amount of delay applied to the live feedback a musician heard from their partner and the degree that this delay varied. The amount of latency and jitter applied to the performance is summarised in the file or directory name for each performance and is described in detail in the above publication. Note that latency and jitter conditions were presented in a random order for each duo.</p> <p><strong>Data collected includes:</strong></p> <ul> <li>audio recordings for each performance, with and without delay, collected via direct line-in (MIDI, WAV).</li> <li>video recordings, collected via high-quality webcams (MKV, AVI).</li> <li>streams of the quarter note pulse provided by each musician in a performance (MIDI).</li> <li>muxed audio-visual recordings of both participants in each performance (MP4)</li> <li>accelerometer and photoplethysmography streams, collected from arm-worn devices (TXT, duos 3-5 only)</li> <li>questionnaire responses from performers, evaluating each condition (XLSX)</li> <li>ratings of performance quality from an unbiased sample of listeners, collected during an online perceptual study (CSV)</li> </ul> <p><strong>Repository structure:</strong></p> <p><strong><em>NB: please see this section of the code documentation website (LINK REMOVED FOR PEER REVIEW) for a full description of how to recreate the analyses and models created in the paper.</em></strong></p> <p>The files <em>data.zip </em>and <em>data.z0*</em> contain all data collected from the study, APART from the perceptual study stimuli & results. To open these files, download the <em>data.zip</em> file and <em><strong>all the corresponding volumes ending in .z0 </strong></em>and open the <em>data.zip</em> file using a tool for opening multi-part zip files, such as WinRAR. <em>Do not try to open the files ending in .z0</em>, otherwise you may get a message about the data being corrupted. Inside <em>data.zip</em>, you'll see the following folders and files:</p> <ul> <li><em>avmanip_output</em>: the raw MIDI, audio, and video output from each performance <ul> <li>the subfolders are organised with a single folder per participant duo, experimental block, and condition.</li> <li>avmanip_output\trial_1\Block 1\Condition 1 - 23 05 relates to the performance of the first duo of participants in the first session of the experiment, in the first condition they encountered, with 23ms of latency and 0.5x jitter.</li> </ul> </li> <li><em>midi_bpm_cleaning</em>: the cleaned MIDI files (quarter note onset positions) <ul> <li>the subfolders are organised similarly to the <em>avmanip_output</em> folder, using the same conventions.</li> </ul> </li> <li><em>muxed_performances</em>: the combined audio-video .mp4 files from each performance <ul> <li>these files are labelled in the format: duo_session_latency_jitter_keysfmt_drumsfmt.</li> <li>muxed_performances\kdelay_ddelay\d1_s1_l23_j00_kdelay_ddelay.mp4 relates to the performance of the first duo of participants in the first session of the experiment, in the first condition they encountered, with 23ms of latency and 0.5x jitter, and with latency and jitter applied to both keys and drummer.</li> <li>for more information on recreating these videos, see the linked section of the code documentation website (LINK REMOVED FOR PEER REVIEW).</li> </ul> </li> <li><em>questionnaire_anonymized</em>: the anonymized questionnaire responses given by participants, also contained in the supplementary material of the associated paper (see preprint).</li> </ul> <p>Alongside <em>data.zip </em>and the <em>data.z0*</em> archives, there are two further loose files, <em>Database View Participant - Dashboard.csv, Database View SuccessTrial - Dashboard.csv, </em>which are the anonymized demographic and response data from the perceptual experiment, and one loose archive folder <em>perceptual_study_videos.rar</em>, which contains the stimuli used in the perceptual experiment.</p> <p><strong>Usage:</strong></p> <p>To reproduce the analysis, models, and graphs from the paper, download the code in code-analysis-modeling.rar and extract it to a new folder, then extract all the files inside <em>data.zip</em> and the two perceptual study CSV files into \data\raw. Install Python 3.10 if you don't have it already, and then open a command prompt in the root directory of the analysis code and execute the command <em>run.cmd</em><em>.</em></p> <p>The remaining code files (<em>code-perceptual-study.rar</em> and <em>code-testbed-software.rar</em>) contain the code used in the perceptual and laboratory experiments. Documentation and installation instructions are provided within each archive.</p> <p>These recordings of live, improvised duo performances are unattributed and anonymized as agreed with participants at the point of data collection. The musicians involved received a one-off, fixed payment for their time and had their travel expenses reimbursed, with funding provided by ANONYMIZED FOR PEER REVIEW. All participants consented to the use of their recordings for projects by the current authors and for these recordings to be shared with interested members of the music psychology community, with the intention of furthering academic research. The musicians did not intend that the recordings be used for commercial, artistic, or entertainment purposes, and such use is not permitted.</p> <p><strong>Citation:</strong></p> <p>If you use this dataset in your research, please follow the citation format posted on GitHub (LINK REMOVED FOR PEER REVIEW).</p> <p><strong>Contact:</strong></p> <p>ANONYMIZED FOR PEER REVIEW</p>
Testing for the Presence of Authorship Bias in Peer Review
ClinicalTrials.gov study NCT02739737. IPD Sharing: NO. Countries: 0. Publications: 6.
Researcher perspectives on publication and peer review of data
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Data from: Gender differences in patterns of authorship do not affect peer review outcomes at an ecology journal
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Data from: Is it becoming harder to secure reviewers for peer review? A test with data from five ecology journals
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Data from: Author-suggested reviewers: gender differences and influences on the peer review process at an ecology journal
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Data from: Editor and reviewer gender influence the peer review process but not peer review outcomes at an ecology journal
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Data from: Gender differences in peer review outcomes and manuscript impact at six journals of ecology and evolution
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Peer-reviewed papers included in topic model of old animal ecology and conservation
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Which peer reviewers voluntarily reveal their identity to authors? Insights into the consequences of open-identities peer review
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Data from: Imbalance in individual researcher's peer review activities quantified for four British Ecological Society Journals, 2003-2010
Researchers contribute to the scientific peer review system by providing reviews, and "withdraw" from it by submitting manuscripts that are subsequently reviewed. So far as we are aware, there has been no quantification of the balance of individual's contributions and withdrawals. We compared the number of reviews provided by individual researchers (i.e., their contribution) to the number required by their submissions (i.e. their withdrawals) in a large and anonymised database provided by the British Ecological Society. The database covered the Journal of Ecology, Journal of Animal Ecology, Journal of Applied Ecology, and Functional Ecology from 2003–2010. The majority of researchers (64%) did not have balanced contributions and withdrawals. Depending on assumptions, 12% to 44% contributed more than twice as much as required; 20% to 52% contributed less than half as much as required. Balance, or lack thereof, varied little in relation to the number of years a researcher had been active (reviewing or submitting). Researchers who contributed less than required did not lack the opportunity to review. Researchers who submitted more were more likely to accept invitations to review. These finding suggest overall that peer review of the four analysed journals is not in crisis, but only due to the favourable balance of over- and under-contributing researchers. These findings are limited to the four journals analysed, and therefore cannot include researcher's other peer review activities, which if included might change the proportions reported. Relatively low effort was required to assemble, check, and analyse the data. Broader analyses of individual researcher's peer review activities would contribute to greater quality, efficiency, and fairness in the peer review system.
Authorship information of open educational resources derived from peer-reviewed scientific literature
<p>This dataset evaluates the authorship of open educational resources available at 5 STEM resource web sites (EcoEd Digital Library, CourseSource, Teaching Issues and Experiments in Ecology, Teach the Earth, and the National Center for Case Study Teaching in Science). Using 20 exercises from each site, it evaluates the proportion of exercises that draw on peer-reviewed scientific studies; of those, it also evaluates the proportion in which any author of the teaching exercise overlaps with any author of a scientific article from which the open educational resource is derived. The overall goal is to evaluate overlap in authorship between scientific publications and associated open educational resources. The first tab shows how the studies were selected and the second tab presents authorship data for each study.</p>
Open peer review in scientific journals indexed in DOAJ (respostas)
<p><span><span>Dados coletados para o desenvolvimento da dissertação, e demais publicações dela provenientes, intitulada "REVISÃO POR PARES ABERTA: PERCEPÇÃO DOS EDITORES DE PERIÓDICOS CIENTÍFICOS INDEXADOS NO DIRECTORY OF OPEN ACCESS JOURNALS" de autoria de Francisca Clotilde de Andrade Maia, sob orientação da Dra. Maria Giovanna Guedes Farias. </span></span></p>
Assessing the Effectiveness of Concurrent Peer Review for Patients With Cardiovascular Disease and Diabetes
ClinicalTrials.gov study NCT00508014. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.