Fish schooling behavior inferred from differences between backscatter levels in Doppler sonar beams
Bibliographic record
Abstract
The general availability of Doppler profilers on survey ships provides a convenient source of acoustic backscatter data. Aside from calibration issues, caution must be exercised when analyzing this data because each of the diverging beams has a different interaction angle with the scatterers. In particular, for targets with directional scattering characteristics a different backscatter strength will be seen in each beam. The availability of data from multiple beam directions can however provide information on scatterer orientation when groups of such scatterers undertake coherent motion. This effect is demonstrated in observations of Norwegian spring spawning herring (Clupea harengus). In data collected while these fish are actively migrating with mean swimming speeds of 20 cm s−1, a difference of 5 dB is seen in volume backscatter strength depending on the direction of fish movement with respect to the acoustic beams. In contrast, in data collected when these fish schools have less well defined movements with a mean swimming speed of less than 10 cm s−1, a difference of less than 1 dB is seen.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".