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Record W2955949563 · doi:10.1016/j.whi.2019.04.011

Evidence Map: Reporting of Results by Sex or Gender in Randomized, Controlled Trials with Women Veteran Participants (2008 to 2018)

2019· article· en· W2955949563 on OpenAlexfundno aff
Elisheva R. Danan, Kristen Ullman, Ruth Klap, Elizabeth M. Yano, Erin E. Krebs

Bibliographic record

VenueWomen s Health Issues · 2019
Typearticle
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsnot available
FundersQuality Enhancement Research InitiativeU.S. Food and Drug AdministrationCanadian Institutes of Health ResearchU.S. Department of Veterans AffairsNational Institute for Health and Care ResearchAgency for Healthcare Research and QualityNational Institutes of HealthOffice of Research and Development
KeywordsMedicineRandomized controlled trialMeta-analysisPsychological interventionSex characteristicsFemale sexDemographyClinical psychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.169
metaresearch head score (Gemma)0.547
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.831
Threshold uncertainty score0.893

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1690.547
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0130.027
Bibliometrics0.0240.023
Science and technology studies0.0020.005
Scholarly communication0.0140.008
Open science0.0050.007
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0150.003

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 head0.273
GPT teacher head0.467
Teacher spread0.194 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designSystematic review
DomainReporting
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

Citations10
Published2019
Admission routes1
Has abstractno

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