An examination of recovery planning for forest-dwelling woodland caribou (<em>Rangifer tarandus caribou</em>) in Ontario, Canada
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".