Investigating visual attention during scene perception of safe and unsafe occupational performance
Bibliographic record
Abstract
BACKGROUND: Occupational therapists routinely use observation for evaluation, intervention planning, and prediction of a client's occupational performance and/or safety within the environment. Perception of safety contributes to the decision-making process for discharge or placement recommendations. PURPOSE: The purpose of this study was to determine if differences exist in safety ratings and eye movements between occupational therapists and nontrained matched individuals while viewing domain-specific versus non-domain-specific images. METHOD: Ten licensed occupational therapists and 10 age-, gender-, and education level-matched participants completed this eye-tracking study. FINDINGS: For all image exposure durations, occupational therapists had more polarized safety ratings for stroke-related image content but little evidence of differences in eye movements between groups. Eye movement group differences did not emerge in the regions of interest identified by an independent expert panel. IMPLICATIONS: The results point to a complex relationship between decision making and observational behaviour in occupational assessment and highlight the need to look beyond image features.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".