MétaCan
Menu
← Back to cohort
Record W1516366262

Canadian Stroke Best Practice Recommendations: Mood, Cognition and Fatigue Following Stroke practice guidelines, update 2015

2015· article· en· W1516366262 on OpenAlexaffabout
Gail A. Eskes, Krista L. Lanctôt, Nathan Herrmann, Patrice Lindsay, Mark Bayley, Laurie Bouvier, Deirdre Dawson, Sandra Egi, Elizabeth Gilchrist, Theresa Green, Gord Gubitz, Michael D. Hill, Tammy Hopper, Aisha Khan, Andrea King, Adam Kirton, Paige Moorhouse, Eric E. Smith, Janet Green, Norine Foley, Katherine Salter

Bibliographic record

VenueQUT ePrints (Queensland University of Technology) · 2015
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsQueen Elizabeth II Health Sciences CentreUniversity of AlbertaUniversity of CalgaryGlenrose Rehabilitation HospitalCollège Communautaire du Nouveau-BrunswickCapital District Health AuthorityUniversity Health NetworkHealth Sciences CentreMoncton HospitalDalhousie UniversityWestern UniversityUniversity of TorontoRoyal Victoria HospitalRiverview HospitalAlberta Children's HospitalToronto Rehabilitation InstituteSunnybrook Health Science CentreHeart and Stroke Foundation
Fundersnot available
KeywordsMoodStroke (engine)GuidelineCognitionMedicineRehabilitationDepression (economics)Best practicePhysical therapyPsychiatryClinical psychology
DOInot available

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.038
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 score0.962
Threshold uncertainty score0.273

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0070.008
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0050.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0170.009

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 head0.035
GPT teacher head0.323
Teacher spread0.287 · 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

Citations9
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueQUT ePrints (Queensland University of Technology)→Same topicStroke Rehabilitation and Recovery→French-language works237,207→