MétaCan
Menu
Back to cohort
Record W2789617795 · doi:10.1177/1715163518756926

A pharmacist checklist for direct oral anticoagulant management: Raising the bar

2018· article· en· W2789617795 on OpenAlexafffundvenue
Kori Leblanc, William Semchuk, John Papastergiou, Blair Snow, Leilany Mandlsohn, Vinay K. Kapoor, Lisa M. Guirguis, James D. Douketis, William Geerts, David J. Gladstone

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2018
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversity of SaskatchewanUniversity of TorontoRegina Qu'Appelle Health RegionUniversity Health Network
FundersBayer CanadaUniversity of AlbertaJanssen Research and DevelopmentSunnybrook Research InstituteServierPfizerMcMaster UniversityUniversity of TorontoUniversity Health NetworkSanofi
KeywordsChecklistPharmacistRaising (metalworking)Bar (unit)Oral anticoagulantMedicinePharmacyWarfarinPsychologyFamily medicineMaterials scienceInternal medicineGeographyMetallurgy

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)0.041
metaresearch head score (Gemma)0.202
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.202
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.002
Science and technology studies0.0090.003
Scholarly communication0.0070.009
Open science0.0060.006
Research integrity0.0130.018
Insufficient payload (model declined to judge)0.0130.005

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 head0.118
GPT teacher head0.360
Teacher spread0.242 · 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

Citations11
Published2018
Admission routes3
Has abstractno

Explore more

Same venueCanadian Pharmacists Journal / Revue des Pharmaciens du CanadaSame topicAtrial Fibrillation Management and OutcomesFrench-language works237,207