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Record W4310456603 · doi:10.1177/00084174221142184

The Multiple Errands Test: A Guide for Site-Specific Version Development

2022· article· en· W4310456603 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Accessibility for Disabilities
Canadian institutionsnot available
Fundersnot available
KeywordsTest (biology)PsychologyPhysical medicine and rehabilitationMedicineGeology

Abstract

fetched live from OpenAlex

Background. The complex and real-world nature of the Multiple Errands Test (MET) makes it a valuable and increasingly popular assessment of cognitive function. However, these same qualities make its local implementation challenging. Purpose. To produce an evidence-based guide for site-specific adaptation of the MET. Method. The CAN-IMPLEMENT © knowledge translation framework informed a structured approach to the creation of a guide to site-specific version development, informed by twenty-two published approaches to MET adaptation. Applicability of the guide was supported by a two-phase revision process, in which a site-specific hospital and community version produced from its recommendations were administered with forty-two neurologically intact participants and stakeholder feedback obtained. Findings. We offer an outline of core components which maintain the integrity of the MET, and adaptable peripheries which may be modified when required by the local setting. Implications. The proposed guide provides a systematic yet flexible guide for site-specific MET development.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.141
GPT teacher head0.371
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