Bibliographic record
Abstract
The capacity of a freeway segment should be measured only when it is an active bottleneck. The properties of flows at active freeway bottlenecks have a bearing on both the definition of capacity and the procedure of capacity analysis. Past studies have examined the flow features at bottlenecks on several freeways in Toronto, Canada, and San Diego, California. This study examined 27 active bottlenecks in the Twin Cities metro area in Minnesota for a 7-week period. The analysis focuses on the properties of prequeue transition flows (PQFs) and queue discharge flows (QDFs) averaged across various time intervals (30-s, daily average, and long-run average). It is found that the proportion by which flows drop after upstream queues form at all studied bottlenecks ranges from 2% to 11%. The 30-s QDFs display high variation and should not be assumed to be constant. The daily average QDFs at each studied bottleneck follow a normal distribution based on two normality tests and visual inspection of the normal probability plot. Results also suggest that the long-run average QDFs [mean of 2,016 passenger cars per lane per hour (pcplph)] and PQFs (mean of 2,124 pcplph) are both normally distributed. The implication of these empirical findings on capacity estimation is also discussed.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".