Bibliographic record
Abstract
Data set for Roche (submitted) Waves affect the escape response of juvenile coral reef fish Abbreviations for colum headers in .xlsx file. Data are organized according to figures in the ms. For any questions about the data, or if you find errors, please contact dominique.roche@mail.mcgill.ca Abstract 1. Fish often escape from predators with a burst of speed (fast-start responses). In laboratory studies, these responses are always measured in stationary water. However, water motion due to waves and currents is ubiquitous in many aquatic systems. 2. In shallow marine habitats, wave action creates unsteady water motion that varies spatially and temporally. This likely affects the ability of fish to escape, especially when they are small. Since body depth is thought to improve postural control and stability, I examined how wave-driven water flow affects the escape response of juvenile coral reef fish in three species of Pomacentridae with different body morphologies. 3. Escape responses were elicited under static or unsteady flow conditions. In unsteady flow, all fish covered a greater distance and reached a higher speed and acceleration when escaping in the direction of the water flow. However, compared to static flow, unsteady flow had no detectable effect on maximum escape performance. 4. Fish took longer to respond to the stimulus in unsteady compared to static flow. This effect differed between species. The fusiform-shaped species responded more slowly in unsteady than in static flow. This difference was less pronounced in the species with an intermediate body depth and absent in the species with a deep body. The deep-bodied species also tended to orient itself more directly into the water flow and was less displaced by water motion. 5. Response latency is a major determinant of escape success, so postural disturbances from unsteady water motion might reduce the ability of some fishes to evade predators during juvenile settlement. This could have important implications for the distribution, abundance and recruitment of reef fishes across spatial and temporal scales.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.084 | 0.016 |
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".