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Record W2423349558 · doi:10.1136/bmj.h5298

Benefits of, and barriers to, reactivating dormant trials

2015· letter· en· W2423349558 on OpenAlexaboutno aff
Ruth Gilbert, Katie Harron, Lorraine Dearden

Bibliographic record

VenueBMJ · 2015
Typeletter
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
FundersEconomic and Social Research CouncilWellcome Trust
KeywordsTreasureLinkage (software)Clinical trialBusinessBiologyGeographyBioinformaticsGenetics

Abstract

fetched live from OpenAlex

The UK should follow Ontario and reactivate its treasure trove of dormant trials to generate new science through linkage with administrative data.1 Many groups stand to benefit. For example, drug regulators could encourage linkage of dormant and new trials to administrative data to monitor long term safety of drugs.2 Linkage would also lead to better evidence on the long …

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)0.103
metaresearch head score (Gemma)0.388
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.897
Threshold uncertainty score0.545

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1030.388
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.002
Science and technology studies0.0040.012
Scholarly communication0.0110.014
Open science0.0040.007
Research integrity0.0640.060
Insufficient payload (model declined to judge)0.0100.007

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 head0.317
GPT teacher head0.489
Teacher spread0.173 · 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
GenreCommentary

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
Published2015
Admission routes1
Has abstractyes

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