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Record W2161699211 · doi:10.1017/s1041610202008050

Assessing Hypertension in the Canadian Study of Health and Aging

2001· article· en· W2161699211 on OpenAlexaffabout
Heather S. Davis, Heather Merry, Chris MacKnight, Kenneth Rockwood

Bibliographic record

VenueInternational Psychogeriatrics · 2001
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineBlood pressureDiseaseStroke (engine)Hypertensive diseaseInternal medicineGerontologyCardiology

Abstract

fetched live from OpenAlex

We investigated the self-report hypertension variables in the CSHA, recorded in the screening questionnaire and the Self-Administered Risk Factor (SARF) questionnaire. The two questions showed high agreement (phi coefficient 0.83). Each was modestly but significantly associated with other simultaneous reports of heart disease and stroke, and with subsequent mortality. Only the SARF asked questions about treatment; controlling for treatment effects, five-year survival was longest among those with no hypertension and no treatment (mean survival time 1,645 days; 95% CI 1,632 to 1,658), and shortest for those with no reported hypertension who were receiving "antihypertensive" medications presumably prescribed for other cardiovascular disease (mean survival time 1,496 days; 95% CI 1,457 to 1,535). The SARF questions incorporating high blood pressure and treatment appear preferable to assess the risks associated with hypertension.

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)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.080
GPT teacher head0.371
Teacher spread0.291 · 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
Published2001
Admission routes2
Has abstractyes

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