The effectiveness of signs at restricting vehicle traffic: a case of seasonal closures on forest access roads
Bibliographic record
Abstract
We assessed the effectiveness of signs that temporally restrict vehicle traffic on forest access roads in northeastern Ontario. The signs specifically prohibit vehicle use of roads in proximity to lakes with remote (i.e., floatplane accessible) tourism during the first 2 weeks of the regular (i.e., rifles, shotguns, and muzzle-loaders) moose ( Alces alces ) hunting season. Vehicle use in restricted areas was measured by counts from traffic monitoring devices during the first 4 weeks of the hunting season (2 weeks during and 2 weeks after the restriction) at 14 sites with signs and another 14 sites without signs. The results suggest that these signs limit some, but not all, traffic in areas during the first 2 weeks of moose hunting. The estimated noncompliance rate with signs was 11.7% with a 95% confidence interval of 4.5% to 24.7%.
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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 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".