Direct Estimation of Early Survival and Movements in Eastern Wolf Pups
Bibliographic record
Abstract
Abstract: Determining juvenile survival and recruitment rates is essential to assess status and viability of animal populations. Currently, the demographic attributes of juvenile carnivores, specifically wolves ( Canis lycaon ), are poorly known but of considerable conservation interest. We measured survival and dispersal rates for 51 juvenile (age 3.5–31 weeks) wolves in Algonquin Provincial Park, Canada, from 2004 to 2005, using implantable very high frequency transmitters. Monthly pup survival was high (0.970, 95% CI = 0.951–0.990) and constant from June to November, and most pup mortality was from natural causes. Pups dispersed as early as age 15 weeks, and monthly dispersal rates were high for young pups (min. = 0.008, 95% CI = 0.000–0.019; max. = 0.030, 95% CI = 0.010–0.050). We failed to detect any influence of pack or litter size on pup survival or probability of dispersal. Radiotelemetry offers an individual‐based monitoring technique capable of providing direct assessment of wolf pup survival and movements, with rigorous estimation of survival and dispersal rates and quantification of cause‐specific mortality.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".