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Record W6925555932 · doi:10.17605/osf.io/gz9ep

SPOR Evidence Alliance: Patient-Driven Research

2023· other· en· W6925555932 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2023
Typeother
Languageen
FieldSocial Sciences
TopicLegal case studies and regulations
Canadian institutionsnot available
Fundersnot available
KeywordsAlliancePublic healthProduction (economics)Context (archaeology)Knowledge productionHealth care

Abstract

fetched live from OpenAlex

The SPOR Evidence Alliance is a pan-Canadian research initiative established in 2017 to address gaps in the production of decision-maker driven knowledge synthesis, as well as development, distribution, and adoption of guidelines in clinical and public health practices. The central aim of the initiative is to foster a collaborative and coordinated approach to building a patient-oriented learning and responsive health system in Canada.

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)0.241
metaresearch head score (Gemma)0.324
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.759
Threshold uncertainty score0.936

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2410.324
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.011
Science and technology studies0.0090.008
Scholarly communication0.0220.007
Open science0.0070.017
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0500.010

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 head0.236
GPT teacher head0.523
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
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

Citations0
Published2023
Admission routes1
Has abstractyes

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