Consensus Statements for Screening and Assessment Tools
Bibliographic record
Abstract
Occupational therapists, both generalists and specialists, have a critical role in providing services to senior drivers. These services include evaluating fitness-to-drive, developing interventions to support community mobility, and facilitating the transition from driving to non-driving when necessary for personal and community safety. The evaluation component and decision-making process about fitness-to-drive are highly dependent on the use of screening and assessment tools. The purpose of this paper is to briefly present the rationale and context for 12 consensus statements about the usefulness and appropriateness of screening and assessment tools to determine fitness-to-drive, within the occupational therapy clinical setting, and their implications on community mobility.
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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 | 0.382 | 0.525 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.014 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".