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Record W2027324119 · doi:10.1503/cmaj.121679

Health care workers must protect patients from influenza by taking the annual vaccine

2012· editorial· en· W2027324119 on OpenAlexvenueno aff
Ken Flegel

Bibliographic record

VenueCanadian Medical Association Journal · 2012
Typeeditorial
Languageen
FieldDecision Sciences
TopicDiverse academic research themes
Canadian institutionsnot available
Fundersnot available
KeywordsPrimum non nocereHarmDo no harmMedicineInfluenza vaccineHealth careVaccinationMedical emergencyFamily medicineNursingIntensive care medicinePsychologyLawVirologyPolitical sciencePsychiatrySocial psychology

Abstract

fetched live from OpenAlex

No right-thinking physician would ever knowingly harm a patient or fail to do some essential thing that would result in harm to a patient. This principle of medical practice is enshrined in the Latin dictum primum non nocere (first, do no harm). But when 55%–65% of physicians fail to take the

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)0.013
metaresearch head score (Gemma)0.055
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: Editorial
Teacher disagreement score0.033
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.055
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0030.002
Science and technology studies0.0050.005
Scholarly communication0.0090.005
Open science0.0050.001
Research integrity0.0330.048
Insufficient payload (model declined to judge)0.0060.006

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 head0.030
GPT teacher head0.373
Teacher spread0.343 · 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

Citations20
Published2012
Admission routes1
Has abstractyes

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