Development of a weighted scoring system for the Electronic Driving Observation Schedule (eDOS)
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.
Bibliographic record
Abstract
The electronic Driving Observation Schedule (eDOS) is a novel approach to assessing older drivers' performance in their everyday driving environment on their chosen routes. The original eDOS total score is generated using the count of driving errors, which does not account for distinct risk levels of different types of driving errors made in different complexity of driving environments. This study was conducted to create one score to represent the complexity of driving route during each eDOS observation and one weighted eDOS total score to represent older drivers' performance accounting for the risk of driving errors by their type and the complexity of maneuvers in their corresponding environments. A literature review, a two-round survey with 13 experts in driving evaluation, and iterative discussions between primary investigators were conducted for generating these scores. Two formulae were created to calculate a weighted maneuver/environmental complexity score and a weighted eDOS total score. •An advanced weighted score is created to represent one's on-road driving performance in their everyday driving environment not only using the count of driving errors, but also accounting for the risk level of each error.•The complexity of driving maneuver and environment in each on-road driving trip can be systematically rated.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it