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Record W2326828534 · doi:10.1177/1747493015622461

<i>Canadian Stroke Best Practice Recommendations</i> : Acute Inpatient Stroke Care Guidelines, Update 2015

2016· article· en· W2326828534 on OpenAlexaffabout
Leanne K. Casaubon, Jean-Martin Boulanger, Ev Glasser, Dylan Blacquière, Scott Boucher, Kyla Brown, Tom Goddard, Jacqueline M. Gordon, Myles Horton, Jeffrey Lalonde, Christian Larivière, Pascale Lavoie, Paul Leslie, Jeanne McNeill, Bijoy K. Menon, Brian Moses, Melanie Penn, Jeffrey J. Perry, Elizabeth Snieder, Dawn Tymianski, Norine Foley, Eric E. Smith, Gord Gubitz, Michael D. Hill, Patrice Lindsay

Bibliographic record

VenueInternational Journal of Stroke · 2016
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsYukon UniversityVictoria General HospitalOntario Brain InstituteUniversité LavalUniversity of ManitobaKingston General HospitalHorizon Health NetworkNova Scotia Health AuthorityDartmouth General HospitalFraser HealthRegina Qu'Appelle Health RegionSaint John Regional HospitalHeart and Stroke FoundationIsland HealthHôpital Charles-Le MoyneUniversity of TorontoUniversité de SherbrookeDalhousie UniversityOttawa HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineStroke (engine)Acute strokeEmergency medicineIntensive care medicineMEDLINEInternal medicineTissue plasminogen activator

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)0.006
metaresearch head score (Gemma)0.040
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: Other · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score0.279

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.040
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0120.019
Science and technology studies0.0040.002
Scholarly communication0.0060.003
Open science0.0050.003
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0160.008

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 head0.019
GPT teacher head0.338
Teacher spread0.319 · 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
GenreOther

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

Citations68
Published2016
Admission routes2
Has abstractno

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