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Record W2164880146 · doi:10.7557/2.28.1.147

An examination of recovery planning for forest-dwelling woodland caribou (<em>Rangifer tarandus caribou</em>) in Ontario, Canada

2008· article· en· W2164880146 on OpenAlexaboutno aff
Christopher J. A. Wilkinson

Bibliographic record

VenueRangifer · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsWoodland caribouGeographyWoodlandPopulationForestryTaigaChristian ministryHabitatEcologyEnvironmental protectionBiologyDemographyPolitical science

Abstract

fetched live from OpenAlex

Ontario’s population of forest-dwelling woodland caribou is listed both federally and provincially as a species at risk. It is estimated that 20 000 woodland caribou remain in Ontario, of which approximately one quarter inhabit the boreal forest and are described as the sedentary forest-dwelling population. This paper examines the recovery strategy for this population developed by the Ministry of Natural Resources, as well as discussing the implications of provincial forestry policy on woodland caribou management. Commercial timber harvesting will likely soon be allowed in parts of the northern third of the province, in which woodland caribou habitat currently is relatively unimpaired by industrial development. Abstract in Norwegian / Sammendrag:Planlegging for bevaring av skogsøkotypen av Rangifer tarandus caribou i Ontario, CanadaSkogsvillreinen av skogsøkotypen i Ontario er vurdert som sårbar både føderalt og på provinsnivå. Av provinsens rundt 20 000 skogsvillrein hører omtrent en fjerdepart til den stasjonære skogsboende skogsøkoypen. Artikkelen ser på bevaringsstrategien som er utarbeidet av naturressursdepartementet i Ontario for denne spesielle bestanden og diskuterer konsekvensene for villreinen av provinsens skogpolitikk. Kommersiell hogst vil mest sannsynlig og snart bli tillatt i deler av Ontarios nordlige tredel der skogvillreinens leveområder er relativt upåvirket av industriell virksomhet.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score1.000

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)0.0010.000

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 head0.216
Teacher spread0.201 · 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

Citations4
Published2008
Admission routes1
Has abstractyes

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