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Record W2516948168 · doi:10.1136/ebmed-2016-110503

Late-life increases in alcohol consumption among postmenopausal women appear associated with greater breast cancer risk and less coronary heart disease risk

2016· letter· en· W2516948168 on OpenAlexaff
Tim Stockwell, Tanya Chikritzhs

Bibliographic record

VenueEvidence-Based Medicine · 2016
Typeletter
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsBreast cancerAlcohol consumptionMedicineCoronary heart diseasePostmenopausal womenInternal medicineDiseaseConsumption (sociology)OncologyCancerCardiologyAlcoholEnvironmental healthBiology

Abstract

fetched live from OpenAlex

Commentary on: Dam M, Hvidtfeldt U, Tjønneland A, et al. Five year change in alcohol intake and risk of breast cancer and coronary heart disease among postmenopausal women: prospective cohort study. BMJ 2016;353:i2314[OpenUrl][1][Abstract/FREE Full Text][2]. The hypothesis that alcohol consumption leads to reduced risk of coronary heart disease (CHD) has immense clinical and public policy implications. Some meta-analyses of observational epidemiological studies have reported that ‘moderate’ alcohol use significantly reduces CHD risk. However, this has been contested on multiple theoretical and empirical grounds,1–3 including arguments that selection biases operating across the life course contribute to a false appearance of CHD protection. Health outcomes for a cohort of postmenopausal women (n=21 523) with average age 62.2 years at baseline were assessed over 11 years from the Danish hospital, death records and cancer register. This sample comprised women who agreed to be interviewed on two separate occasions 5 years apart, representing 81% of those enrolled … [1]: {openurl}?query=rft.jtitle%253DBMJ%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.i2314%26rft_id%253Dinfo%253Apmid%252F27169583%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=353/may11_9/i2314&atom=%2Febmed%2F21%2F5%2F195.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.

How this classification was reachedexpand

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
Observationallow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.004
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0040.001
Research integrity0.0160.011
Insufficient payload (model declined to judge)0.0330.017

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 head0.077
GPT teacher head0.334
Teacher spread0.256 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Not applicable
Domainnot available
GenreEmpirical · Commentary

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

Citations1
Published2016
Admission routes1
Has abstractyes

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