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Record W2064358067 · doi:10.5014/ajot.56.3.350

Occupation in Stressful Times

2002· article· en· W2064358067 on OpenAlexaffabout
Mary Ann McColl

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2002
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsIconCitationDownloadOccupational therapyOnline searchLibrary scienceComputer sciencePsychologyWorld Wide WebPsychiatry

Abstract

fetched live from OpenAlex

Article| Online May 01 2002 Occupation in Stressful Times Mary Ann McColl Mary Ann McColl Mary Ann McColl, PhD, OT(C), is Professor, Division of Occupational Therapy, Queen's University, Kingston, Ontario K7L 3N6, Canada; mccollm@post.queensu.ca Search for other works by this author on: This Site PubMed Google Scholar Author & Article Information Online Issn: 1943-7676 Print Issn: 0272-9490 Copyright © 2002 by the American Occupational Therapy Association, Inc.2002 The American Journal of Occupational Therapy, 2002, Vol. 56(3), 350–353. https://doi.org/10.5014/ajot.56.3.350 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share MailTo Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Mary Ann McColl; Occupation in Stressful Times. Am J Occup Ther May/June 2002, Vol. 56(3), 350–353. doi: https://doi.org/10.5014/ajot.56.3.350 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentThe American Journal of Occupational Therapy Search Advanced Search This content is only available via PDF. Copyright © 2002 by the American Occupational Therapy Association, Inc.2002 Article PDF first page preview Close Modal You do not currently have access to this content.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.204
GPT teacher head0.501
Teacher spread0.297 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations26
Published2002
Admission routes2
Has abstractyes

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