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Record W1999793317 · doi:10.1136/bmj.330.7498.1021

Readers guide to critical appraisal of cohort studies: 3. Analytical strategies to reduce confounding

2005· review· en· W1999793317 on OpenAlexafffund
Sharon‐Lise T. Normand, Kathy Sykora, Ping Li, Muhammad Mamdani, Paula A. Rochon, George Anderson

Bibliographic record

VenueBMJ · 2005
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of TorontoInstitute for Clinical Evaluative Sciences
FundersCanadian Institutes of Health Research
KeywordsConfoundingLogistic regressionProportional hazards modelOutcome (game theory)Critical appraisalEconometricsStatisticsSelection biasCohortPropensity score matchingCohort studyMedicineMathematics

Abstract

fetched live from OpenAlex

Department of Health. Health inequalities-national targets on infant mortality and life expectancy-technical briefing

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)0.053
metaresearch head score (Gemma)0.302
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: Review · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.420

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.302
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0180.013
Science and technology studies0.0010.003
Scholarly communication0.0040.005
Open science0.0070.004
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.1260.099

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 head0.657
GPT teacher head0.637
Teacher spread0.020 · 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
GenreReview

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

Citations171
Published2005
Admission routes2
Has abstractyes

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