MétaCan
Menu
Back to cohort
Record W2508988151 · doi:10.22621/cfn.v130i2.1842

The History of Elk (<i>Cervus canadensis</i>) Restoration in Ontario

2016· article· en· W2508988151 on OpenAlexafffundvenueabout
Josef Hamr, Frank F. Mallory, Ivan Filion

Bibliographic record

VenueThe Canadian Field-Naturalist · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsLaurentian UniversityCambrian College
FundersOntario Ministry of Natural Resources and ForestryMinistry of Natural Resources
KeywordsGeographyCensusPopulationPopulation growthFisheryDemographyArchaeologyBiology

Abstract

fetched live from OpenAlex

Elk (Cervus canadensis) historically inhabited southern Quebec and central Ontario, but, by the early 1900s, the species was extirpated from this region. Attempts to re-establish an Elk population in Ontario during the first half of the 20th century had limited success. We reviewed historical documents, population census records, and a previous study pertaining to Elk reintroduced to Ontario in the early 1900s for clues to the cause(s) of their limited population growth. After an apparent rapid population increase in the 1940s followed by unregulated hunting during the subsequent 3 decades, Elk abundance in Ontario had not appreciably changed from 1970 to 1997, most likely because of the small founding population, unsustainable hunting, and accidental mortality. After the abolition of legal hunting in 1980, natural mortality appeared to be the main limiting factor. A limited sample of pregnancy and calf recruitment rates, body measurements, and physical condition parameters collected in 1993–1997, suggested that adults were healthy, reproducing successfully, and not limited by food availability; thus, it was concluded that remnant Elk populations could be augmented by introducing additional animals. A renewed Elk restoration effort, conducted from 1998 to 2001, imported 443 Elk from Elk Island national Park in Alberta to 4 release areas across central Ontario (Lake of the Woods, Lake Huron North Shore, Nipissing/French River, and Bancroft/North Hastings), resulting in a provincial population of about 800 Elk by 2013.

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)0.001
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 score0.035
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.012
GPT teacher head0.187
Teacher spread0.175 · 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

Citations2
Published2016
Admission routes4
Has abstractyes

Explore more

Same venueThe Canadian Field-NaturalistSame topicRangeland and Wildlife ManagementFrench-language works237,207