POPULATION ECOLOGY OF COLUMBIAN BLACK-TAILED DEER IN URBAN VANCOUVER, WASHINGTON
Bibliographic record
Abstract
Abstract Little is known of the population ecology of black-tailed deer in urban environments. We investigated blacktail survival, productivity, and population rate-of-increase in urban Vancouver, Washington, from 1999 to 2001. We captured and radio-tagged 19 deer and located radio-tagged deer 1 to 4 times per week. Average annual survival pooled over 2 y was 0.70 (sx̄ = 0.09) for does and 0.86 (sx̄ = 0.12) for bucks. The majority of deer mortality (5 of 6) was due to trauma from collisions with either cars (n = 3) or trains (n = 2); the remaining death was likely an illegal kill. Adult does produced a minimum of 1.83 and 1.36 fawns in 1999 and 2000, respectively. Minimum fawn survival was calculated as 0.69 (sx̄ = 0.09) by assuming that all fawns died whose mother was killed after weaning. Maximum potential fawn survival was calculated as 0.84 (sx̄ = 0.08) by censoring fawns whose mothers were killed after weaning. Demographic analysis indicated that the deer population was producing a surplus of young and was increasing at an annual rate of ≥16%/y.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".