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Record W7099421217

TERMS OF REFERENCE Background and Rationale

2013· article· en· W7099421217 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicUkraine: War, Education, Health
Canadian institutionsnot available
Fundersnot available
KeywordsExcellenceDelegateAccountabilityPatient careVariety (cybernetics)Quality (philosophy)AccreditationResource (disambiguation)
DOInot available

Abstract

fetched live from OpenAlex

training of undergraduate medical students, postgraduate medical trainees and physician assistant trainees, but relies on the affiliated hospitals to provide the venue and significant resources for these programs. Undergraduate medical students in the Faculty of Medicine spend significant time in the hospital setting. In 3rd and 4th years, medical students spend almost all of their time in the hospitals and a variety of other sites outside campus buildings. The Royal College of Physicians and Surgeons and the Canadian College of Family Physicians delegate the responsibility for postgraduate medical education to the University of Toronto. In turn, the Faculty of Medicine places the postgraduate trainees into the teaching environment of the affiliated teaching hospitals for the entire tenure of their training program. The hospitals are responsible for high quality patient care including that provided by medical students and clinical trainees, under the supervision of the clinical faculty. In order to facilitate the planning and resource allocation necessary to sustain excellence of our medical education programs, a senior education advisory committee comprising hospital and Faculty of Medicine education leadership is appropriate and necessary. Accountability The Committee is advisory to the Dean of the Faculty of Medicine, University of Toronto.

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)0.011
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.724
Threshold uncertainty score0.923

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.061
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.009
Science and technology studies0.0040.003
Scholarly communication0.0080.007
Open science0.0050.004
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.2760.196

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 head0.037
GPT teacher head0.276
Teacher spread0.239 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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Same topicUkraine: War, Education, HealthFrench-language works237,207