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Record W6977495972 · doi:10.6084/m9.figshare.25763086

Additional file 2 of Harmonization of clinical practice guidelines for primary prevention and screening: actionable recommendations and resources for primary care

2024· article· en· W6977495972 on OpenAlexaff

Bibliographic record

VenueFigshare · 2024
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsUniversity of CalgaryCollege of Physicians and Surgeons of OntarioMemorial University of NewfoundlandOntario Institute for Cancer ResearchAlberta Health ServicesWomen's College HospitalCanadian Cancer SocietyUniversity of TorontoUniversity of Alberta
Fundersnot available
KeywordsPrimary careHarmonizationClinical PracticeMEDLINEPrimary health carePrimary prevention

Abstract

fetched live from OpenAlex

Additional file 2: Appendix 2. Summary of Search Results.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptInsufficient payload (model declined to judge)
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
grokInsufficient payload (model declined to judge)
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
opusno category
Domain: not available · Genre: Dataset
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
models splitAgreement compares identical category sets and study designs across arms.

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)0.005
metaresearch head score (Gemma)0.100
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.908
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.100
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.012
Science and technology studies0.0010.000
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.9080.188

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 head0.375
GPT teacher head0.534
Teacher spread0.159 · 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

Labeled directly by 3 models reading the full record.

Insufficient payload (model declined to judge)

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable
Domainnot available
GenreOther · Dataset

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
Published2024
Admission routes1
Has abstractyes

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