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Record W2138571613 · doi:10.1136/ebmed-2014-110086

Mendelian randomisation meta-analysis sheds doubt on protective associations between ‘moderate’ alcohol consumption and coronary heart disease

2014· letter· en· W2138571613 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEvidence-Based Medicine · 2014
Typeletter
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsUniversity of Victoria
FundersEconomic and Social Research CouncilMedical Research Council
KeywordsConfoundingObservational studyMedicineMendelian randomizationInternal medicineAlcohol consumptionMeta-analysisGenotypeAlcoholGeneticsBiologyGeneGenetic variants

Abstract

fetched live from OpenAlex

Commentary on : Holmes M, Dale C, Zuccolo L, et al. Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data. BMJ 2014;349:g4164.[OpenUrl][1][Abstract/FREE Full Text][2] A protective association between low-dose alcohol and risk of coronary heart disease (CHD) has been suggested by meta-analyses of observational studies and experimental studies. Observational studies are, however, vulnerable to residual confounding and selection bias. Compared with observational studies, the Mendelian randomisation (MR) approach can mitigate confounding, is immune to reverse causation, and is consistent with intention-to-treat principles since ‘quitting’ a genotype is impossible. The MR approach relies on the random assignment of genetic variants (genotypes) at meiosis to randomly allocate participants to exposures (eg, alcohol consumption) known to be affected by those genotypes. Holmes and colleagues applied an MR meta-analysis design to data from 56 studies, including 260 000 participants of European ancestry. A variant … [1]: {openurl}?query=rft.jtitle%253DBMJ%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.g4164%26rft_id%253Dinfo%253Apmid%252F25011450%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=bmj&resid=349/jul10_6/g4164&atom=%2Febmed%2F20%2F1%2F38.atom

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Meta-analysislow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Meta-analysislow
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.809
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.395
GPT teacher head0.433
Teacher spread0.037 · 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