The complexity of narrowband echo envelopes as a function of fish side-aspect angle
Bibliographic record
Abstract
Abstract Burwen, D. L., Nealson, P. A., Fleischman, S. J., Mulligan, T. J., and Horne, J. K. 2007. The complexity of narrowband echo envelopes as a function of fish side-aspect angle. – ICES Journal of Marine Science, 64: 1066–1074. High-frequency, narrowband acoustic signals may contain more information on fish size and orientation than previously thought. Our observations of dual frequency identification sonar (DIDSON) images of fish orientation paired with split-beam echo envelopes helped clarify why metrics such as echo duration have performed better than target strength measurements when predicting salmon lengths at side aspect. Fish orientation has a pronounced effect on the duration and shape of split-beam echo envelopes from large (80–130 cm) salmon insonified at side aspect. At near-normal aspect angles, echo envelopes are unimodal, symmetrical, and resemble echo envelopes from calibration spheres. With increasing oblique-aspect angle, echo shapes become less symmetrical as the number of peaks increases, and echo duration and amplitude become more variable. Using angle and range coordinates, peaks in an echo envelope can be traced to their origin on a DIDSON image. At oblique-aspect angles, discrete peaks develop that are reflected from regions close to the head and tail. In addition, the distance between peaks increases with increasing aspect angle and is larger than can be explained by swimbladder length.
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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 | 0.002 |
| 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".