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Record W1991570465 · doi:10.1016/s0895-4356(00)00210-9

Choice of effect measure for epidemiological data

2000· article· en· W1991570465 on OpenAlexaff
Stephen D. Walter

Bibliographic record

VenueJournal of Clinical Epidemiology · 2000
Typearticle
Languageen
FieldMathematics
TopicAdvanced Causal Inference Techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRelative riskNumber needed to treatMeasure (data warehouse)StatisticsEconometricsMedicineAbsolute risk reductionOdds ratioStatistical modelConfidence intervalMathematicsActuarial scienceComputer scienceData miningEconomics

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)0.114
metaresearch head score (Gemma)0.285
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.886
Threshold uncertainty score0.603

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1140.285
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0070.004
Science and technology studies0.0010.004
Scholarly communication0.0050.008
Open science0.0050.005
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.821
GPT teacher head0.668
Teacher spread0.153 · 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 designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations196
Published2000
Admission routes1
Has abstractno

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