Efficacy of Visual Encounter Surveys for Coastal Tailed Frog Detection
Bibliographic record
Abstract
Abstract Coastal tailed frogs Ascaphus truei inhabit montane streams and forested habitats in the Coast and Cascade mountains from northern California to the Skeena River watershed in northwestern British Columbia. Terrestrial adults and juveniles of this cryptic biphasic species are difficult to survey as they are small, do not vocalize, and may be associated with woody ground structures or subsurface refugia at considerable distances from natal streams. We performed a comparative analysis of the detection rate of postmetamorphic coastal tailed frogs and ecological factors hypothesized to influence detection when conducting visual encounter and pitfall trap surveys. We conducted concurrent surveys in northwestern British Columbia at six sites over similar time periods using both techniques. The average detection rate of visual encounter surveys (mean = 0.249, SD = 0.702) was greater than that of pitfall sampling (mean = 0.138, SD = 0.773) when cool temperatures and high humidity favor aboveground movement during the daytime. Light-touch ground searches of refuge habitats likely enhanced detection during visual surveys. Although the average detection rate was less, pitfall traps provided 24-h sampling and were less affected by the experience of the surveyor and the occurrence of ground cover. In general, variation in seasonal behavior influenced detection regardless of method. The relatively higher cost and fixed nature of pitfall traps should be weighed against the ability to apply more cost-effective visual encounter surveys to a greater number of sites.
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".