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Record W2151034010 · doi:10.1371/journal.pmed.0050177

Mendelian Randomisation and Causal Inference in Observational Epidemiology

2008· article· en· W2151034010 on OpenAlexfundaboutno aff
Nuala A. Sheehan, Vanessa Didelez, Paul R. Burton, Martin D. Tobin

Bibliographic record

VenuePLoS Medicine · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsnot available
FundersEuropean CommissionUniversity of LeicesterMedical Research CouncilGenome Canada
KeywordsMendelian randomizationObservational studyCausal inferenceConfoundingInferenceEpidemiologyMarginal structural modelMedicineBiologyGeneticsComputer scienceInternal medicinePathologyArtificial intelligence

Abstract

fetched live from OpenAlex

Translation discusses health interventions in the context of translation from basic to clinical research, or from clinical evidence to practice.

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)0.228
metaresearch head score (Gemma)0.458
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.228
Threshold uncertainty score0.952

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2280.458
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0110.006
Bibliometrics0.0070.009
Science and technology studies0.0020.007
Scholarly communication0.0040.005
Open science0.0070.004
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0090.002

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 head0.130
GPT teacher head0.340
Teacher spread0.210 · 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
Domainnot available
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

Citations392
Published2008
Admission routes2
Has abstractyes

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