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Translating evidence from multiple guidelines into evidence-informed clinical practice protocols for remote symptom assessment, triage and support - the COSTaRS project

2011· article· en· W2313660133 on OpenAlexaff
Dawn Stacey, Kathryn Nichol, Meg Carley, Gail Macartney, D. A. Bakker, Kimberly Chapman, Dauna Crooks, Garnet Cummings, E Green, Doris Howell, Craig Kuziemsky, Brenda Sabo, Myriam Skrutkowski, Ann Syme, Chris Tayler, Tracy Truant, M B Harrison

Bibliographic record

VenueInternational Journal of Evidence-Based Healthcare · 2011
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsLaurentian UniversityQueen's University
Fundersnot available
KeywordsTriageEvidence-based practiceMedicineMedical educationClinical PracticeEvidence-based medicineDecision aidsPsychologyMedical emergencyFamily medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

s of the 2011 Joanna Briggs Institute International Convention: Mission Impossible? Evidence based practice and the future of global health: 7–9 November 2011, National Wine Centre, Adelaide, South Australia: ABSTRACTS

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)0.602
metaresearch head score (Gemma)0.717
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.602
Threshold uncertainty score0.491

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.6020.717
Meta-epidemiology (narrow)0.0020.004
Meta-epidemiology (broad)0.0060.008
Bibliometrics0.0120.010
Science and technology studies0.0030.004
Scholarly communication0.0180.010
Open science0.0080.024
Research integrity0.0090.013
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 head0.692
GPT teacher head0.623
Teacher spread0.069 · 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.

Study designNot applicable
Domainnot available
GenreProtocol

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

Citations0
Published2011
Admission routes1
Has abstractyes

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