Adjustment of submerged swimming to changes in buoyancy in cormorants
Bibliographic record
Abstract
Waterbirds are buoyant because of volumes of air in their plumage and respiratory tract. When they are submerged, their buoyancy is reduced, owing to compression of these volumes of air with depth. We tested how the horizontal submerged swimming of cormorants (Phalacrocorax carbo sinensis (Blumelbach, 1798)) changed when their buoyancy was artificially reduced. Birds were filmed swimming under water once with lead weights (density 11 000 kg·m–3) and again with "dummy" weights (density 1100 kg·m–3) attached to their body. The dummy weights had negligible weight under water and served as control for the increased drag in the experiment. Cormorants swimming with weights tilted their bodies at an angle of 3°–7° below the swimming direction, whereas the body of birds in the control groups was tilted at 14°–16°. The tilt of the body affected the orientation and trajectory of the tail and feet during swimming. A hydrodynamic analysis showed that the lesser tilt of the body (while swimming with weights equivalent to 26% of body weight) resulted in a 55%–57% reduction of the vertical hydrodynamic forces (lift, drag, and thrust) generated by the birds to overcome buoyancy. When more weights were added and the birds became negatively buoyant, these vertical forces changed direction to prevent sinking. Thus, by adjusting the tilt of the body, the birds may dynamically control their buoyancy to maintain straight horizontal swimming despite changes in buoyancy.
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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".