Defining Freeway Capacity as Function of Breakdown Probability
Why this work is in the frame
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Bibliographic record
Abstract
The need for an enhanced freeway capacity definition that incorporates the probabilistic nature of the freeway breakdown process is addressed. This is investigated through an extensive analysis of speed and volume data collected at two freeway bottleneck sites in Toronto, Ontario, Canada. At each site, the freeway breakdown process was examined in detail for more than 40 congestion events occurring during the course of nearly 20 days. Preliminary models were developed for each site. These models are used to describe the probability of breakdown versus the observed flow rate and to examine the implications that this probabilistic approach to breakdown has on the current definition of freeway capacity. A revised, probabilistic freeway capacity definition is proposed for use in future editions of the Highway Capacity Manual.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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