Performance and maneuverability of three species of teleostean fishes
Bibliographic record
Abstract
Whole-animal behavior and performance are assembled from functional capabilities that are dependent on morphology, such as body form and fin-distribution patterns. We compared hovering, median and paired fin (MPF), body and caudal fin (BCF), and burst-and-coast gaits and maneuvers permitted within these gaits, turning, backward swimming, and braking for three species: goldfish, Carassius auratus, silver dollar, Metynnis hypsauchen, and angelfish, Pterophyllum scalare. Goldfish have a fusiform body with a relatively small surface area and depth. Silver dollars and angelfish had larger areas and depths. The smaller surface area was expected to be associated with greater use and higher speeds in BCF swimming behaviors for goldfish but little support was found. Larger body depth was expected to be associated with higher turning rates and maneuverability of silver dollars versus goldfish, but data were again equivocal. Body depth may be more important in defense than in locomotion. Goldfish and silver dollars have ventral paired fins. Angelfish have more derived lateral pectoral fins, anterior pelvic fins, and larger median fins. This fin pattern was expected to be associated with greater use of MPF behaviors at higher speeds, and with greater maneuverability. Support for this expectation was found, but there were sufficient exceptions to indicate that other factors were important.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".