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Record W2105931519 · doi:10.1139/x08-074

The effectiveness of signs at restricting vehicle traffic: a case of seasonal closures on forest access roads

2008· article· en· W2105931519 on OpenAlexafffundvenueabout
Len M. Hunt, Steven Hosegood

Bibliographic record

VenueCanadian Journal of Forest Research · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsLakehead UniversityMinistry of Natural Resources and Forestry
FundersMinistry of Natural Resources
KeywordsGeographySpeed limitForestryEnvironmental scienceArchaeology

Abstract

fetched live from OpenAlex

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%.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.058
GPT teacher head0.332
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2008
Admission routes4
Has abstractyes

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