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Record W4405625085 · doi:10.1016/s0140-6736(24)02666-7

Integrating environmental outcomes in randomised clinical trials: a call to action

2024· article· en· W4405625085 on OpenAlexaff
Johanne Juul Petersen, Linn Hemberg, Lehana Thabane, Sally Hopewell, An‐Wen Chan, Asbjørn Hróbjartsson, Ole Mathiesen, Myles Sergeant, Sujane Kandasamy, Nandi Siegfried, Paula Williamson, Lisa Fox, Caroline Barkholt Kamp, Jean‐Marc Hoffmann, Stig Brorson, Peter Bentzer, Janus Christian Jakobsen

Bibliographic record

VenueThe Lancet · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsMcMaster UniversityWomen's College HospitalUniversity of TorontoBrock UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsCall to actionMedicineClinical trialAction (physics)Randomized controlled trialMEDLINEInternal medicineBiologyBusiness

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)0.749
metaresearch head score (Gemma)0.871
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.251
Threshold uncertainty score0.310

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.7490.871
Meta-epidemiology (narrow)0.0060.007
Meta-epidemiology (broad)0.0360.020
Bibliometrics0.0110.013
Science and technology studies0.0070.061
Scholarly communication0.0450.068
Open science0.0280.026
Research integrity0.1320.104
Insufficient payload (model declined to judge)0.0170.005

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 head0.351
GPT teacher head0.492
Teacher spread0.140 · 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 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

Citations17
Published2024
Admission routes1
Has abstractno

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