IDENTIFICATION OF ANDEAN FELID FECES USING PCR-RFLP
Bibliographic record
Abstract
Scat analysis is a useful method to determinedistribution, abundance and diet of animals(Putman, 1984; Kohn and Wayne, 1997;Wasser et al., 2004). These methods are par-ticularly relevant for monitoring elusive andsecretive carnivores for which feces are oftenthe only available materials (Foran et al., 1997;Riddle et al., 2003). As feces of similar-sizedcarnivore species can resemble each other inmorphology and composition, distinguishingamong them can be problematic (Davidson etal., 2002; Prugh and Ritland, 2005). Develop-ment of methods for identification of the spe-cies from which feces originated is crucial forscat collection-based monitoring programs.DNA methods on scat use intestinal cells ofthe animal that are incorporated into feces.Molecular scatology has been demonstratedto be an efficient method to identify carnivorespecies in a large number of publications,including felids (e.g. Farrel et al., 2000; Ernestet al., 2000; Palomares et al., 2002; Wan et al.,2003; Zuercher et al., 2003). However, no pro-tocol specific to Andean felids has been pub-lished. Several projects focussing on Andeancat (
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".