MétaCan
Menu
Back to cohort
Record W4392066733 · doi:10.51644/9780889206199-002

In Memoriam

2006· book-chapter· en· W4392066733 on OpenAlexaboutno aff
Morris M. Schnore

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicHistory of Medical Practice
Canadian institutionsnot available
Fundersnot available
KeywordsPhilosophyArtComputer science

Abstract

fetched live from OpenAlex

Morris Modris Schnore died July 6, 1984, at his home in London, Ontario, after a long, courageous battle with cancer.Born in Latvia, Dr. Schnore experienced many of the miseries of the Second World War, finally immigrating to Canada in 1947 as a Displaced Person.After working for a year as a lumberjack in Kapuskasing he travelled to London, Ontario, to attend the University of Western Ontario where he received an Honours B. A. and M.A. in psychology in 1952 and 1954, respectively.In 1957 he received his Ph.D. from McGill University, following which he returned to the University of Western Ontario where he was a faculty member in the Department of Psychology for twenty-seven years.He was noted for his enthusiastic presentations in his courses and his personal interest in the education and careers of his students.Dr. Schnore's earliest research interests and publications dealt with memory function.Subsequently, these interests expanded into the effects of aging on memory and competence and attitudes toward retirement.His studies were published in professional journals and were presented to a wide variety of professional societies both in Canada and abroad.As well, he made many presentations to community groups and organizations on the subject of aging, especially as it relates to retirement.This book represents the culmination of many years of research.

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)0.001
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0940.055

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 head0.023
GPT teacher head0.281
Teacher spread0.258 · 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
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
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicHistory of Medical PracticeFrench-language works237,207