Assessment of behavioral energetics model on <i>Puma concolor</i> using doubly labeled water
Bibliographic record
Abstract
The estimation of energy expenditure is key to resolve ecological questions and conservation strategies. The puma ( Puma concolor (Linnaeus, 1771)) has been the subject of several efforts to measure the daily energy expenditure (DEE). Most of the estimations have been made using movement or activity models that have been questioned because of discrepancies with kill rates. This study looks at one movement model estimation and validates it using doubly labeled water (DLW), which can also account for energy expenditures beyond those associated with activity. We captured six pumas (51.5 ± 9.9 (SD) kg) during the winter in Colorado that were GPS collared and injected with DLW for an approximately 3-week trial. We found that DEE obtained from the DLW (14.5 ± 6.1 MJ·day−1) did not differ from that estimated using the movement model or from the predicted allometric equation based on DLW studies on other mammals. Decreasing air temperature and increasing daily distance movement were correlated with increasing DEE for monitored pumas. Both DLW and movement models provide a reasonable proxy to estimate DEE at the population level but exhibit low precision in estimating individual values for free-ranging puma.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".