Flight energetics of the Marbled Murrelet,<i>Brachyramphus marmoratus</i>
Bibliographic record
Abstract
We measured flight speeds (n = 3000) of Marbled Murrelet, Brachyramphus marmoratus (J.F. Gmelin, 1789), to determine whether flight speeds of an exceptionably fast bird coincide with the maximum-range speeds (Vmr) predicted by aerodynamic theory. The mean (±SE) speed of 22.6 ± 0.21 m·s–1was significantly higher than the Vmrpredicted by four models, using conventional values for the parasite drag coefficient (CDpar). In order for the Penny cuick model to predict a Vmrof 22 m·s–1, a CDparof 0.05, which is lower than any previously reported, is necessary; the other models would need to assume even lower values for CDpar. We concluded that the cruising speed of Marbled Murrelets exceeds Vmr. Marbled Murrelets may exceed Vmras a result of behavioural decisions, and we examined two behavioural hypotheses: that flight speeds exceed Vmrto (1) minimize predation rate and (2) maximize chick growth rate. However, there was no significant difference between flight speeds during high (daylight) and low (darkness) predation periods or between chick-rearing and non-breeding periods. Marbled Murrelets may also appear to fly at a speed that exceeds Vmrbecause the underlying aerodynamic theory is inaccurate for this species. To examine the reliability of aerodynamic theory for Marble Murrelets, we compared measured wingbeat frequencies (f) to those predicted by Pennycuick's model. The mean f was significantly lower than the frefpredicted by Pennycuick's model, and generally, f = 7.9m–0.22is a better model for auks than Pennycuick's model. In addition, the Strouhal number was particularly low (0.12 ± 0.02). We conclude that the current aerodynamic models are insufficient for an exceptionally fast-flying bird.
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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 | 0.001 |
| 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".