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Record W2152421298 · doi:10.12927/hcq.2013.21627

Health Indicators 2009: A Focus on Cardiac Care in Canada

2010· article· en· W2152421298 on OpenAlexaffabout
Yana Gurevich, Tina LeMay, Dragos Capan, Jeremy Herring

Bibliographic record

VenueHealthcare Quarterly · 2010
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsCanadian Institute for Health Information
Fundersnot available
KeywordsFalling (accident)MedicineHealth careMedical emergencyCardiovascular healthEmergency medicineEnvironmental healthDiseaseEconomic growthInternal medicineEconomics

Abstract

fetched live from OpenAlex

Close to 18,000 Canadians die each year after having had a heart attack. Heart attacks are costly to the system: ischemic heart disease (including heart attacks) cost the Canadian healthcare system $8.1 billion in 2000. The Canadian Institute for Health Information's recently released Health Indicators 2009 includes new information relating to heart attacks. This article highlights some of the key findings from the report related to cardiac care. It examines the declining rates of for heart attacks, socio-economic factors relating to heart attacks, falling 30-day in-hospital mortality rates and trends and provincial differences in cardiac procedures.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.089
Threshold uncertainty score0.643

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.016
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.012
GPT teacher head0.320
Teacher spread0.307 · 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

Citations2
Published2010
Admission routes2
Has abstractyes

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