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2008· article· en· W4250574314 on OpenAlexaboutno aff

Bibliographic record

VenueInternational Journal of Therapy and Rehabilitation · 2008
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Occupational therapySociologyMedical educationPsychologyLibrary scienceMedicineVisual artsArtComputer sciencePhysical therapy

Abstract

fetched live from OpenAlex

This easy-to-read textbook is intended for occupational therapy (OT) educators, post-graduate students and practitioners. The text is laid out as a collection of essays which are intended to be linked together by the common thread of complexity theory, however, it was hard to follow that thread across chapters. The book was written by OT ’theorists from around the world all of whom have embraced the challenge of complexity’ (p.xviii). These experts were selected because they were seen to be at the cutting edge of theory and its application to practice. The edited text is written by 11 authors from four countries (Hong Kong, New Zealand, South Africa and the UK) which could be construed as international but does not include any Australian, American or Canadian authors, resulting in a unique perspective on some occupational therapy issues.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.518
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0060.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.4820.357

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 head0.172
GPT teacher head0.485
Teacher spread0.313 · 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.

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
Published2008
Admission routes1
Has abstractyes

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