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Record W2140980043 · doi:10.1080/01421590802064880

Neuroanatomy: a single institution study of knowledge loss

2008· article· en· W2140980043 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMedical Teacher · 2008
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsGraduation (instrument)Medical educationBlameCohortPsychologyNeuroanatomyMedical schoolMultiple choiceEducational measurementMathematics educationMedicineCurriculumPedagogyPsychiatryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Most of the literature on neuroanatomy education has focused on its instructional method. Little is known about the retention of acquired knowledge in the basic neurosciences upon graduation from medical school. METHODS: Twenty-four graduating medical students at the University of Saskatchewan, Canada answered 20 multiple-choice questions from the original first year neuroanatomy midterm examination, 33 months after the original exam date. The course involved 58 instructional hours in the dissecting lab and classroom during the first year of medical school. RESULTS: Relative knowledge loss in this cohort was 60%, and the mean multiple-choice exam score dropped from 82% to 33%. Two students received passing grades on the retest (50% and 55%) and the rest failed. CONCLUSIONS: Most graduating medical students were unable to pass a first year exam in the basic neurosciences. Lack of knowledge reinforcement and poor applicability to the clinical setting may be to blame, and suggests that teaching foundational concepts, useful for general practice, are more worthwhile.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.596

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)0.0010.000

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 head0.022
GPT teacher head0.252
Teacher spread0.230 · 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