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Record W4309735726 · doi:10.31219/osf.io/85nqb

Sex and gender considerations in a COVID-19 clinical trials registry

2022· preprint· en· W4309735726 on OpenAlexafffund
Amédé Gogovor

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsClinical trialCoronavirus disease 2019 (COVID-19)MedicineFamily medicineDemographyPathologySociologyDisease

Abstract

fetched live from OpenAlex

To assess “sex” and “gender” considerations in registered COVID-19 clinical trials. The data source was the WHO International Clinical Trails Registry Platform for COVID-19 trials registry (retrieved on 28 July 2020). Sex- and gender-related terms were searched in relevant fields of the registry. A content analysis was conducted. Less than one per cent of the trials (<1%) used sex- and gender-related terms in the title.

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 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)0.317
metaresearch head score (Gemma)0.568
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.683
Threshold uncertainty score0.843

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3170.568
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0120.019
Science and technology studies0.0010.002
Scholarly communication0.0050.007
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0190.003

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 head0.696
GPT teacher head0.598
Teacher spread0.098 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
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

Citations0
Published2022
Admission routes2
Has abstractyes

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