Assessing the Validity of the Accelerometry Technique for Estimating the Energy Expenditure of Diving Double-Crested Cormorants<i>Phalacrocorax auritus</i>
Bibliographic record
Abstract
Over the past few years, acceleration-data loggers have been used to provide calibrated proxies of energy expenditure: the accelerometry technique. Relationships between rate of oxygen consumption and a derivation of acceleration data termed "overall dynamic body acceleration" (ODBA) have now been generated for a range of species, including birds, mammals, and amphibians. In this study, we examine the utility of the accelerometry technique for estimating the energy expended by double-crested cormorants Phalacrocorax auritus to undertake a dive cycle (i.e., a dive and the subsequent pause at the surface before another dive). The results show that ODBA does not calibrate with energy expenditure in diving cormorants, where energy expenditure is calculated from measures of oxygen uptake during surface periods between dives. The possible explanations include reasons why energy expenditure may not relate to ODBA but also reasons why oxygen uptake between dives may not accurately represent energy expenditure during a dive cycle.
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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 | 0.004 | 0.013 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".