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Record W1767653448 · doi:10.1136/bmj.h3293

Diabetes is rising in OECD countries, report warns

2015· article· en· W1767653448 on OpenAlexaboutno aff
J. Wise

Bibliographic record

VenueBMJ · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsMember statesDiabetes mellitusDiseaseMedicineObesityEconomic growthDeveloped countryCause of deathDevelopment economicsEnvironmental healthPolitical scienceBusinessInternational tradeEuropean unionEconomicsPopulation

Abstract

Deaths from cardiovascular disease have fallen by over 60% in the past 50 years in the Organisation for Economic Cooperation and Development (OECD) member states, but rising levels of obesity and diabetes threaten the prospects of further improvement, a new report warns. Cardiovascular Disease and Diabetes: Policies for Better Health and Quality of Care 1 said that cardiovascular disease remains the leading cause of death in OECD countries. The OECD comprises 34 countries including the United States, Canada, Australia, Japan, Korea, Mexico, Chile, and a number of European countries. About 85 million people have diabetes in OECD countries, representing around 7% of people aged 20-79. However, …

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: about_only · design weight: 3321.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: editorial/commentary
about Canada: no
confidence: high

News item reporting an OECD report on rising diabetes; the object is population health, not research practice.

GPT-5.6 (high)OUT
genre: other
about Canada: no
confidence: high

This news report concerns diabetes and public health policy, not the research system.

Grok 4.5OUT
genre: editorial/commentary
about Canada: no
confidence: high

News-style report on rising diabetes in OECD countries; public health news, not metaresearch.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.106
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0080.004

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 head0.063
GPT teacher head0.344
Teacher spread0.281 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations3
Published2015
Admission routes1
Has abstractyes

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