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Record W2409523672 · doi:10.1017/s0317167100051398

Neuropathology in Canada: The First One Hundred Years

2010· review· en· W2409523672 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2010
Typereview
Languageen
FieldMedicine
TopicHistory of Medical Practice
Canadian institutionsUniversity of CalgaryUniversity of Manitoba
Fundersnot available
KeywordsNeuropathologyPeriod (music)GerontologyHistoryPsychologyMedicineArtPathologyDisease

Abstract

fetched live from OpenAlex

We describe the evolution of neuropathology in Canada, beginning with William Osler who began working in Montréal in 1874 and finishing with the major period of expansion in the 1970s. Organized services began in the 1930s, in Montréal with the neurosurgeons Wilder Penfield and William Cone, and in Toronto with Eric Linell and Mary Tom, who both began their careers as neuroanatomists. Jerzy Olszewski and Gordon Mathieson, who trained in Montréal and Toronto, drove the creation of the Canadian Association of Neuropathologists in 1960. Training guided by the Royal College of Physicians and Surgeons of Canada was formalized in 1965, with the first certifying examination in 1968 and the subsequent creation of formal structured training programs. The number of neuropathologists in Canada increased rapidly through the 1960s and 1970s, with individuals coming from both clinical neuroscience and anatomic pathology backgrounds, a pattern that persists to the present day.

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)0.008
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.834
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0020.011
Scholarly communication0.0000.001
Open science0.0040.000
Research integrity0.0010.009
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 head0.077
GPT teacher head0.309
Teacher spread0.233 · 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