Simulation and experimental measurement of side-aspect target strength of Atlantic salmon (<i>Salmo salar</i>) at high frequency
Bibliographic record
Abstract
Numerical simulations and empirical measurements of swimming Atlantic salmon (Salmo salar) were used to describe the effects of fish behavior on side-aspect target strength (TS). Simulation results were based on the numerical solution of the Helmholtz equation with the finite element method (FEM). A three-dimensional geometric model approximated the shape of the swimbladder of an Atlantic salmon. Numerical simulations were used to study the dependence of TS on the fish length, orientation, and swimming behavior. The results showed strong variation in TS, both when the side-aspect angle was changed and when the swimbladder was bent to the direction of the sonar beam. A total of 11 swimming adult Atlantic salmon 62107 cm long were measured with a horizontally aimed echosounder (200 kHz) and video camera, and the experimental results were compared with the corresponding simulation results. The linear regression between mean TS and the logarithm of fish length (L, cm) was TS = 24.4log10(L) 72.9 dB. The strong variability of TS owing to the orientation and bending of the fish and large L/λ ratios reduces the usefulness of TS alone for fish size estimation or species discrimination.
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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 | 0.000 | 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".