MétaCan
Menu
Back to cohort
Record W2795726517 · doi:10.1674/0003-0031-179.2.275

Reproductive Ecology of Recently Established Wild Pigs in Canada

2018· article· en· W2795726517 on OpenAlexaffabout
Erin L. Koen, Eric Vander Wal, Ruth A. Kost, Ryan K. Brook

Bibliographic record

VenueThe American Midland Naturalist · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of SaskatchewanMemorial University of Newfoundland
Fundersnot available
KeywordsLitterBiologyRange (aeronautics)PopulationSex ratioReproductionZoologyEcologyDemography

Abstract

fetched live from OpenAlex

An essential component of management efforts to control invasive species is the estimate of life history parameters, such as reproductive rate and litter size. Wild pigs (Sus scrofa), one of the most invasive terrestrial mammals worldwide, have recently become established on the Canadian prairies. We estimated life history traits in a population of wild pigs in Saskatchewan, Canada, at the current northern limit of their North American distribution. The average pregnant wild pig weighed 73.8 kg (46 – 130 kg; n = 7). Fifty-four percent of females ≥46 kg were pregnant in Feb., with an average of 5.6 fetuses per pregnant female (range 4 – 7; n = 7). Although small sample sizes precluded statistical significance, we found that larger females in better body condition tended to have more fetuses and that the sex ratio of fetuses tended to be female-biased. Based on the cohort that we sampled in Feb., we predicted parturition would occur between Feb. and May; this range of parturition dates may have been wider had we sampled wild pigs at other times of the year. We show that the number of fetuses of wild pigs in Saskatchewan is similar to other areas, suggesting that population growth and spread could be just as rapid. Our estimates represent the first empirical life history measures of wild pigs in Canada and are an essential step in developing science-based eradication plans for this highly invasive species.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.657

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 studies0.0000.001
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 head0.213
Teacher spread0.207 · 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.

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

Citations8
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueThe American Midland NaturalistSame topicWildlife Ecology and ConservationFrench-language works237,207