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Record W1495014175 · doi:10.1002/cncy.21485

An historic step for advanced cytopathology training in Canada

2014· article· en· W1495014175 on OpenAlexaffabout
Manon Auger, Shahidul Islam, Michele Weir

Bibliographic record

VenueCancer Cytopathology · 2014
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsLondon Health Sciences CentreWestern UniversityOttawa HospitalUniversity of OttawaMcGill University Health Centre
Fundersnot available
KeywordsCytopathologyMedicineCompetence (human resources)Medical educationTraining (meteorology)PathologyManagementCytology

Abstract

fetched live from OpenAlex

Advanced cytopathology training has finally obtained official recognition in Canada, having recently been assigned the newly developed status of “Area of Focused Competence” by the Royal College of Physicians and Surgeons of Canada. It is hoped that the trainees who graduate from these programs in cytopathology will be provided with the leadership and consultant skills to allow them to adapt and respond competently to the rapid evolving field of cytopathology.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.332
Teacher spread0.302 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations2
Published2014
Admission routes2
Has abstractyes

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