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Open Minds, Open Opportunities

2012· article· en· W3176841950 on OpenAlexaboutno aff
Richard L. Drake

Bibliographic record

VenueThe FASEB Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsApprehensionCurriculumTheme (computing)Medical educationMedicinePolitical sciencePedagogySociologyPsychology

Abstract

fetched live from OpenAlex

During the last decade of the 20th Century and the first decade of the 21st Century curricular reform has been a popular theme. In fact, reform on the current scale has not occurred since the early 1900's after Abraham Flexner released his landmark report “Medical Education in the United States and Canada”. His report, suggesting major changes in how physicians were educated, became the norm and has generally stayed intact until the last 20 years. During that time increased demands on medical school curriculums related to the explosion of knowledge in biomedical sciences and the pressure to add additional clinical experiences have increased the momentum for curriculum reform. For the educator in the anatomical sciences curricular reform has been a time of excitement, fear, apprehension, etc. How have these curricular changes affected education in the anatomical sciences? And, what types of innovative teaching activities have anatomists developed that mesh with the philosophy for educating physicians in the 21st century?

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)0.005
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.042
Scholarly communication0.0120.019
Open science0.0010.008
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0170.003

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 head0.166
GPT teacher head0.400
Teacher spread0.234 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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