Seasonal detection rates of river otters (Lontra canadensis) using bridge-site and random-site surveys
Bibliographic record
Abstract
Randomization of survey sites is generally desired because of its unbiased approach, but is often abandoned because of logistical constraints. This is true for river otters ( Lontra canadensis (Schreber, 1777)), with bridges commonly determining survey locations. We conducted seasonal sign surveys for river otters on two rivers in southern Missouri, USA, using randomized survey points and fixed bridge-crossing points in 2001–2003. Otter sign was more likely to be detected at randomized sites than at bridge sites in summer (P < 0.0001), with sign being detected on 68% of visits to random sites (n = 348) and on 40% of visits to bridge sites (n = 60). Scat abundance was higher (P = 0.0001) at random sites (8.82 ± 0.6, mean ± SE) than at bridge sites (3.96 ± 1.0) during the summer. Similar but nonsignificant trends were found during the winter. Detection probabilities were significantly higher at random sites than at bridge sites in both seasons. Our results indicate that surveys of bridge sites for river otters may yield inaccurate results for distribution and relative abundance, particularly if conducted during the summer.
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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 | 0.002 | 0.004 |
| 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 | 0.000 | 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".