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Record W381783085 · doi:10.22621/cfn.v118i1.884

Seasonal Home Ranges of Raccoons, <em>Procyon lotor</em>, Using a Common Feeding Site in Rural Eastern Ontario: Rabies Management Implications

2004· article· en· W381783085 on OpenAlexafffundvenueabout
Sarah C. Totton, Richard C. Rosatte, Rowland R. Tinline, Laura L. Bigler

Bibliographic record

VenueThe Canadian Field-Naturalist · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsQueen's UniversityMinistry of Natural Resources and Forestry
FundersQueen's UniversityMinistry of Natural Resources
KeywordsHome rangeAnimal scienceRabiesPopulationVeterinary medicineGeographyBiologyDemographyMedicine

Abstract

fetched live from OpenAlex

Thirteen adult Raccoons (Procyon lotor) (six females, seven males) that fed at a garbage dump north of Kingston, Ontario were radio-tracked from 21 June to 16 October 1995 to assess their seasonal home ranges and movements. Average Minimum Convex Polygon (MCP) summer and fall home ranges for the collared Raccoons were 78.4 ha (SD=46.2 ha) and 45.6 ha (SD=29.7 ha), respectively. Average grid cell summer and fall home ranges for the collared Raccoons were 143.3 ha (SD=40.0 ha) and 116.9 ha (SD=24.9 ha), respectively. Summer ranges of the Raccoons were significantly larger than fall ranges using both the MCP method (P=0.05) and the grid cell method (P=0.073). Yearling Raccoons travelled an average summer maximum distance from the dump of 2608 m (SD=1964, n=3), more than double the distance of adults (≥2 yr) at 1239 m (SD=547, n=10). The population density for the study area in late August 1995 was estimated at 1 Raccoon/12 ha based on an effective area surrounding the dump of 234 ha. Home range and movement data may be useful to design a strategy to control Raccoon rabies in Ontario.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.299
Threshold uncertainty score0.602

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.240
Teacher spread0.223 · 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
Published2004
Admission routes4
Has abstractyes

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