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Record W1482744664 · doi:10.1108/10650750510612443

Cognitive task analysis

2005· article· en· W1482744664 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.

Bibliographic record

VenueOCLC Systems & Services · 2005
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsMcGill University
Fundersnot available
KeywordsUsabilityTask (project management)Computer scienceCognitive walkthroughCognitionWeb usabilityOriginalityPluralistic walkthroughUsability engineeringTask analysisKnowledge managementProcess managementHuman–computer interactionPsychologyEngineeringSystems engineering

Abstract

fetched live from OpenAlex

Purpose To introduce a cognitive approach – cognitive task analysis (CTA) – for the usability evaluation of evidence‐based nursing (EBN) websites. Design/methodology/approach With the justification of the need for new evaluation methodologies for the usability of EBN websites and the provision of the theoretical framework and implications of CTA, the author proposes detailed steps for the usability evaluation of EBN websites. Findings CTA is a new approach that can be used for the evaluation of the usability of EBN websites. It has the advantages that conventional evaluation methods lack in characterizing the aspects of websites useful to nurses in carrying out evidence‐based practices. Originality/value This paper, with the introduction of a new cognitive approach, helps ensure the effective evaluation of the EBN websites, which can then be improved to adequately meet the requirements and information processing needs of the nurses practising evidence‐based nursing.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.005

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 head0.088
GPT teacher head0.490
Teacher spread0.402 · 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