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Record W4376643335 · doi:10.46747/cfp.6905309

Offer CME and accelerate licensing

2023· letter· en· W4376643335 on OpenAlexvenueno aff
Paul Zalan

Bibliographic record

VenueCanadian Family Physician · 2023
Typeletter
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic shortageImmigrationPopulationData scienceMedicineMedical educationFamily medicineComputer sciencePolitical scienceEnvironmental healthLaw

Abstract

fetched live from OpenAlex

Regarding 3-year residency,[1][1] the aims are good. The timing is disastrous. With a shortage of doctors now, the population further growing by 1.5 million from immigration in the next 3 years,[2][2] and with 17.5% of survey respondents in one study planning on retiring in the next 5 years,[3][3]

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)0.016
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: Editorial · Consensus signal: none
Teacher disagreement score0.251
Threshold uncertainty score0.841

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0030.004
Open science0.0020.005
Research integrity0.0190.012
Insufficient payload (model declined to judge)0.2510.136

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 head0.062
GPT teacher head0.307
Teacher spread0.245 · 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
GenreEditorial

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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