Achieving population goals in a long-lived wildlife species (Equus caballus) with contraception
Bibliographic record
Abstract
The ultimate goal of any wildlife contraceptive effort is some alteration of the target population, either through a slowing of growth, or stabilisation or reduction of the population. Early population models suggested that short-term contraceptive agents applied to long-lived species would not achieve significant population changes. Native porcine zona pellucida antigen (PZP), a short-term contraceptive vaccine, was applied to a herd of wild horses inhabiting Assateague Island National Seashore, MD, USA, over a 13-year period, with an immediate goal of achieving zero population growth, a secondary goal of reducing the population from 175 to 150 and a tertiary goal of reaching 120 individuals, all without the physical removal of animals. Contraceptive efficacy ranged from 92 to 100% on an annual basis (96.28 ± 2.49%), and the percentage of adult females that was treated on any given year ranged from 42 to 76% (67.78 ± 18.21%). The goal of zero population growth was achieved in 2 years, an initial decline in the population became apparent in 8 years and by Year 11, the population declined to 135, a decrease of 22.8%. The lengthy period required for achieving a population decline was caused by increasing body condition scores, reduced mortality and significantly increased longevity among treated females.
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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 | 0.001 |
| 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".