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Record W2408572623 · doi:10.1097/opx.0000000000000908

Transparency in Biomedical Research

2016· article· en· W2408572623 on OpenAlexaboutno aff
Michael D. Twa

Bibliographic record

VenueOptometry and Vision Science · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicAcademic Publishing and Open Access
Canadian institutionsnot available
Fundersnot available
KeywordsTransparency (behavior)CompendiumPublic relationsBest practiceMedicinePolitical scienceGeographyLaw

Abstract

fetched live from OpenAlex

Evidence-based practice depends upon the availability of reliable evidence and a priority for the journal is to provide a forum for the best available evidence related to optometry. Over the past 10 years, a number of guidelines have been developed to help authors present their work so that others can clearly follow the methods, results, and interpretations provided. The most extensive collection of guidelines are provided by the Equator network (http://www.equator-network.org/).1,2 The Equator network (Enhancing Quality and Transparency of Health Research) was founded in 2008 and was initially funded as a part of the National Health Service in the United Kingdom in 2006. Since then, three national centers were established in the UK, Canada, and France for the purpose of expanding awareness of reporting guidelines and encouraging best-practices for the reporting of research outcomes. The equator network’s website contains a library of 316 different guidelines and protocols for reporting research results from almost every conceivable study design. This compendium of resources gets pretty specific and one example is #311: Recommendations for reporting economic evaluations of haemophilia prophylaxis. That gives a flavor of how specific the guidelines have become, which I think begs several questions—where does this end, what is the value of this approach, moreover, what is the value of adopting these recommendations as a part of OVS publication standards. In fact, the most used reporting guidelines relate to the main study types also published by Optometry and Vision Science: case reports, diagnostic/prognostic studies, quality improvement studies, observational studies, randomized trials, systematic reviews, and qualitative research. Each of the reporting guidelines have a common thread, encouraging transparency so that published research can be understood and thereby rendered more useful to others. Authors can increase the likelihood of successful publication in Optometry and Vision Science if they follow the reporting guidelines provided through the equator network. What journal editors, authors, methodologists, and others have learned over the years is that reporting guidelines encourage better reporting of research results and this ultimately increases the size and quality of the pool of available evidence. Second, familiarity and use of reporting guidelines has a positive impact on the quality of the research reported by influencing studies at the design stage. Optometry and Vision Science has a history of publishing exotic and obscure conditions as case reports. The value of these case reports to readers of the journal is questionable. For this reason, in January, I began discussions with the Clinical Associate Editor, Dr. Larry Alexander, and Editorial Board Member, Dr. Andrew Mick, about the future of the journal’s clinical content. Several of the journals in our field, e.g. American Journal of Ophthalmology, recently created separate journals as a venue for clinical case reports. Others, have discontinued case reports altogether. To be clear, quality clinical content is valuable to Optometry and Vision Science and the goal is to push for standards that will encourage higher quality and greater relevance for the readers of our journal. To accomplish these goals, the journal will be moving toward new standards for case reports that will be in line with the CARE guidelines recommended by the equator network (http://www.equator-network.org/reporting-guidelines/care).3,4 This will include timeline figures and a more thorough review of existing evidence-based recommendations for diagnostic considerations, treatment options, and prognosis. My vision for the journal includes clinical content with broader appeal and greater impact. Michael D. Twa Editor-in-Chief Optometry and Vision Science

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.048
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.739
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0480.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.014
Science and technology studies0.0000.003
Scholarly communication0.0010.004
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.168
GPT teacher head0.613
Teacher spread0.445 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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