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Record W4386715850 · doi:10.46747/cfp.6909620

Reduce unnecessary routine vitamin D testing

2023· article· en· W4386715850 on OpenAlexaffvenue
Alexander Singer, Christopher McChesney

Bibliographic record

VenueCanadian Family Physician · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsWestern UniversityUniversity of Manitoba
Fundersnot available
KeywordsClothingMedicineVitamin D and neurologyVitaminComputer scienceGerontologyGeographyInternal medicineArchaeology

Abstract

fetched live from OpenAlex

> Laura is a 40-year-old engineer of eastern European ancestry who presents to your office to request testing of her vitamin D levels. She generally wears sunscreen in the summer and wears sun-protective clothing year round. She is fairly healthy, eating a balanced diet high in fresh fruits and

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)0.002
metaresearch head score (Gemma)0.030
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: Commentary · Consensus signal: none
Teacher disagreement score0.102
Threshold uncertainty score0.340

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.1020.021

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 head0.558
GPT teacher head0.489
Teacher spread0.068 · 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
GenreCommentary

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

Citations3
Published2023
Admission routes2
Has abstractyes

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