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Record W2077878878 · doi:10.1016/s0828-282x(09)70021-2

Peripheral arterial disease: Lack of awareness in Canada

2009· article· en· W2077878878 on OpenAlexafffundvenueabout
Marge Lovell, Kenneth D. Harris, Thomas L. Forbes, Gwen Twillman, Beth L. Abramson, Michael H. Criqui, Paul C. Schroeder, Emile R. Mohler, Alan T. Hirsch

Bibliographic record

VenueCanadian Journal of Cardiology · 2009
Typearticle
Languageen
FieldMedicine
TopicPeripheral Artery Disease Management
Canadian institutionsSt. Michael's HospitalWestern UniversityLondon Health Sciences Centre
FundersCordisNovartis Pharmaceuticals CanadaOffice of Public Health and ScienceOmron HealthcareSanofiEli Lilly CanadaGlaxoSmithKlineEli Lilly and CompanyBristol-Myers SquibbAstraZenecaNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsMedicineStroke (engine)PopulationDiseaseRandom digit dialingDiabetes mellitusMyocardial infarctionIntermittent claudicationArterial diseaseTelephone surveyBlood pressurePublic healthVascular diseasePhysical therapyGerontologyInternal medicineEnvironmental healthPathology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.306

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.023
GPT teacher head0.263
Teacher spread0.240 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations105
Published2009
Admission routes4
Has abstractno

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