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Record W2330037092 · doi:10.1097/mbp.0000000000000113

Measuring blood pressure

2015· article· en· W2330037092 on OpenAlexaffabout
Marie‐Éve Leblanc, Lyne Cloutier, Paul Poirier

Bibliographic record

VenueBlood Pressure Monitoring · 2015
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsUniversité du Québec à Trois-RivièresInstitut Universitaire de Cardiologie et de Pneumologie de QuébecUniversité Laval
Fundersnot available
KeywordsMedicineUniversity hospitalBlood pressureGerontologyLibrary scienceInternal medicine

Abstract

fetched live from OpenAlex

aInstitut Universitaire de Cardiologie et de Pneumologie bFaculty of Pharmacy, Laval University, Laval cDepartment of Nursing, University of Quebec at Trois-Rivières, Trois-Rivières, Québec, Canada Correspondence to Paul Poirier, MD, PhD, FRCPC, FACC, FAHA, Institut Universitaire de Cardiologie et de Pneumologie de Québec (IUCPQ), 2725 Chemin Sainte-Foy, QC, Canada G1V 4G5 Tel: +1 418 656 4767; fax: +1 418 656 4581; e-mail: [email protected] Received November 19, 2014 Accepted January 9, 2015 Accepted January 22, 2015

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)0.002
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.091
GPT teacher head0.282
Teacher spread0.191 · 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
GenreMethods

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
Published2015
Admission routes2
Has abstractyes

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