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Record W4400559506 · doi:10.1136/bmjmed-2024-000984

Fostering diversity in clinical trials: need for evidence and implementation to improve representation

2024· editorial· en· W4400559506 on OpenAlexaff
David Collister, Claire Song, Shannon M. Ruzycki

Bibliographic record

VenueBMJ Medicine · 2024
Typeeditorial
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsDiversity (politics)Clinical trialInclusion (mineral)Representation (politics)Quality (philosophy)PsychologyMedicinePolitical scienceSocial psychologyEpistemologyPathologyLaw

Abstract

fetched live from OpenAlex

> The clinical trials community needs better guidance to translate ambitious diversity commitments into actual inclusion and diversity in clinical trials The lack of diversity in clinical trials undermines the generalisability, quality, and external validity of medical research.[1][1] Depending on

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)0.173
metaresearch head score (Gemma)0.441
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.827
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1730.441
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0050.003
Science and technology studies0.0060.011
Scholarly communication0.0230.022
Open science0.0070.005
Research integrity0.0370.056
Insufficient payload (model declined to judge)0.0110.008

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 head0.853
GPT teacher head0.761
Teacher spread0.092 · 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 designNot applicable
DomainMethods
GenreEditorial

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

Citations11
Published2024
Admission routes1
Has abstractyes

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