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Additional file 1: of Differing association of alcohol consumption with different stroke types: a systematic review and meta-analysis

2016· article· en· W6977702162 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2016
Typearticle
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsnot available
Fundersnot available
KeywordsCohortAlcohol consumptionProspective cohort studyCohort studyStroke (engine)Relative riskAssociation (psychology)Consumption (sociology)

Abstract

fetched live from OpenAlex

Text S1. Methods for the Cohort of Swedish Men and Swedish Mammography Cohort. Table S1. Age-standardized baseline characteristics by alcohol consumption in the Cohort of Swedish Men and Swedish Mammography Cohort. Table S2. Relative risks of ischemic stroke, intracerebral hemorrhage, and subarachnoid hemorrhage according to alcohol consumption in the Cohort of Swedish Men and the Swedish Mammography Cohort. Table S3. Relative risks of stroke types for light-to-moderate and high-to-heavy alcohol consumption, stratified by alcohol intake reference group. Figure S1. Newcastleâ Ottawa Scale for prospective cohort studies: Details of how the criteria were applied for prospective studies of the association of alcohol consumption with stroke. Figure S2. Flow chart of study selection (DOCX 202Â kb)

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)0.005
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score0.361

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.071
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0060.009
Science and technology studies0.0010.000
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.7470.028

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 head0.134
GPT teacher head0.341
Teacher spread0.207 · 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 designMeta-analysis
Domainnot available
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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