QUANTIFYING ERRORS ASSOCIATED WITH USING PREY SKELETAL STRUCTURES FROM FECAL SAMPLES TO DETERMINE THE DIET OF STELLER'S SEA LION (<i>EUMETOPIAS JUBATUS</i>)
Bibliographic record
Abstract
Abstract We examined the digestion and passage times of bones and other hard parts from pollock, herring, salmon, and sandlance recovered from two juvenile captive Steller's sea lions (Eumetopias jubatus) subjected to varying activity levels. Key bones that could be identified to species were distributed over an average of 3.2 scats (range 1–6) following a single meal, with pollock remains occurring in significantly more scats than other species. Relying on otoliths alone to determine the presence of prey resulted in significantly fewer prey being identified than if other structures were also used (such as vertebrae, jaw bones, and teeth), particularly for salmon. Using either technique, there were significant differences in the likelihood that bones would be recovered from the series of scats produced following a meal, with pollock recovery exceeding herring (by three‐fold) and sandlance (by eight‐fold). Differences between species were reduced when recovery was calculated on a per scat basis rather than over multiple scats. Active animals passed greater numbers of bones, but the overall effect on prey recovery estimates was not significant. Defecation times of prey structures from a meal were variable and ranged from an initial 2–56 h to a final 28–148 h. The time interval to pass 95% of recovered structutes varied by a factor of two among prey species, and was highest for pollock due to retention beyond 65 h.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".