An overview of experimental Gray Wolf (<i>Canis lupus</i>) poisoning programs in northern Ontario, 1956 to 1964
Bibliographic record
Abstract
In the late 1950s, the Ontario Department of Lands and Forests commenced an experimental Gray Wolf (Canis lupus) poisoning program in northern Ontario, the results of which were documented in a series of unpublished reports. Most projects consisted of distributing baits poisoned with strychnine on frozen lakes in late winter; 12 were conducted by district staff and typically consisted of <10 bait stations monitored for two to four months. An intensive three-year program was completed in the Allanwater area, about 250 km north of Thunder Bay, where up to 56 bait stations were distributed on a grid covering >25 000 km2. Thirty eight wolf kills were reported in the district projects and 81 in the Allanwater study. In total, where sex was identified 56% were male and 44% female. Adults made up 51% of the kill in the Allanwater study, subadults (<2 years old) 44%, and 5% were of unknown age. Two hundred and sixty five kills of species other than wolves were documented from all studies, comprising 10 mammal and nine bird species. Common Raven (Corvus corax) and Red Fox (Vulpes vulpes) made up 54% and 24% of the non-target mortality, respectively, and were recorded in most studies. Kills of wolves and non-target species were probably under-reported because animals left bait stations before dying, were buried by snow, were removed by bounty hunters, or monitoring for non-target species was poor. Although completed over 50 years ago, the studies summarized here provide context on the ecological impacts and ethics of poison use to control wolves.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".