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Record W2036925783 · doi:10.1139/z99-223

Demography and body condition of coyotes (<i>Canis latrans</i>) in eastern New Brunswick

2000· article· en· W2036925783 on OpenAlexvenueaboutno aff
Mathieu Dumond, Marc‐André Villard

Bibliographic record

VenueCanadian Journal of Zoology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsCanisBiologyDemographyScarsPopulationReproductive successEcologyMedicineSurgery

Abstract

fetched live from OpenAlex

We documented the demography and body condition of coyotes (Canis latrans), using 77 carcasses collected in late fall and winter (1995-1996 and 1996-1997) during an increase in snowshoe hare (Lepus americanus) density in eastern New Brunswick. We compared body condition at the beginning (November-January) and end of winter (February-March) in relation to breeding status. Physical characteristics of coyotes were similar to those reported elsewhere in the northeastern portion of its range. The sex ratio did not differ significantly from 1:1. The population was unusually old (5.6 ± 0.4 years of age (mean ± SE)). The parturition rate was low (40.9% in adult females), and placental scars were present only in females >5 years old (6.6 ± 0.6 scars per female). There was no significant decrease in the body condition of adult females over the winter but the body mass of those females with placental scars tended to decrease over the winter (P = 0.012). Also, during November-January, reproductive females (with placental scars) were significantly heavier (P = 0.007) than non-reproductive adult females (without placental scars). Our results suggest that in the coyote populations in eastern New Brunswick, breeding status and reproductive costs should be taken into account in future studies of demography and body condition. Also, the low level of coyote exploitation by humans may be responsible for the old age structure of the population and the low parturition rate. The exploitation level should be considered when analyzing coyote sociodemographic data.

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 score0.368
Threshold uncertainty score0.740

Distilled classifier scores by category (both heads)

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

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 head0.006
GPT teacher head0.191
Teacher spread0.185 · 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

Citations17
Published2000
Admission routes2
Has abstractyes

Explore more

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