Comparison of techniques for sex determination of American martens
Bibliographic record
Abstract
Abstract Accurate determination of sex in harvested species is critical for understanding demography and developing population models for management. We used genetic‐based sex identification to assess accuracy of external carcass and pelt examination at registration and maximum canine root area (MRA) to determine sex of American martens (Martes americana) trapped in the Upper Peninsula of Michigan, 2000–2004. Overall percent similarity between MRA and genetic‐based sex determination was 98.4% (n = 188). In contrast, only 84.6% (n = 421) of martens were similarly classified using external examination. For external examination, percent similarity to genetic‐based sex determination for juveniles (<1‐yr old) and adults (≥1‐yr old; Wald χ21 = 2.168, P = 0.141), as well as for males and females (Wald χ21 = 0.005, P = 0.946), was similar. We recommend MRA as a suitable technique for sex determination of martens; thus, marten sex and age (using cementum annuli counts) can be obtained from one lower canine tooth. We do not recommend use of external examination at registration to identify sex of martens without implementing additional quality assurance measures. © 2010 The Wildlife Society.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".