MétaCan
Menu
Back to cohort
Record W2585873057 · doi:10.1016/j.cjca.2017.01.021

The Gap Between Manual and Automated Office Blood Pressure Measurements Results at a Hypertension Clinic

2017· article· en· W2585873057 on OpenAlexaffvenue
Félix Rinfret, Lyne Cloutier, Hélène L'Archevêque, Martine Gauthier, Mikhael Laskine, Pierre Larochelle, Monica Ilinca, Leora Birnbaum, Nathalie Ng Cheong, Robert Wistaff, Paul Nguyen, Ghislaine O. Roederer, Michel Bertrand, Maxime Lamarre-Cliché

Bibliographic record

VenueCanadian Journal of Cardiology · 2017
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité du Québec à Trois-RivièresUniversité de MontréalMontreal Clinical Research Institute
Fundersnot available
KeywordsMedicineBlood pressureContext (archaeology)CohortCohen's kappaCohort studyKappaInternal medicineClinical trialRetrospective cohort studyNuclear medicinePhysical therapySurgeryStatistics

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)0.018
metaresearch head score (Gemma)0.085
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 score0.041
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.085
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.109
GPT teacher head0.316
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.

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

Citations18
Published2017
Admission routes2
Has abstractno

Explore more

Same venueCanadian Journal of CardiologySame topicBlood Pressure and Hypertension StudiesFrench-language works237,207