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Record W1704063768 · doi:10.22621/cfn.v121i3.474

Road-kill of Mammals in Nova Scotia

2007· article· en· W1704063768 on OpenAlexafffundvenueabout
David Fudge, Bill Freedman, Michael Crowell, Tony Nette, Vince Power

Bibliographic record

VenueThe Canadian Field-Naturalist · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaDalhousie UniversityU.S. Department of Transportation
KeywordsPorcupineNova scotiaWildlifeGeographyZoologyFisheryEcologyBiologyArchaeology

Abstract

fetched live from OpenAlex

We examined road mortality of wild mammals in Nova Scotia using data from (a) five years of province-wide data on wildlife collisions involving larger mammals, and (b) 20 months of observations of smaller mammals along a 160-km route near Halifax. An average of 2079 White-tailed Deer was reported killed annually on highways during 1999 through 2003, along with 14 Moose and 33 Black Bear. Female White-tailed Deer were more likely to be road-killed than males (by a factor of 1.8), yearlings more so than older animals, and there were peaks of mortality in the late spring and late autumn. The road-kill of smaller mammals was highest in the summer and least in the winter, and the most frequent mortalities were of Raccoon (28% of observations), Porcupine (27%), Skunk (17%), Snowshoe Hare (6%), Coyote (4%), and Groundhog (3%). The standardized kill-rate (number/100 km) was highest on a 100-series highway compared to trunk highways or urban streets, but the rate standardized to vehicle density was highest on trunk highways.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.014
GPT teacher head0.242
Teacher spread0.228 · 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 teacher head, not a consensus.

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

Citations12
Published2007
Admission routes4
Has abstractyes

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