Capelin TS: Effect of individual fish variability
Bibliographic record
Abstract
Capelin (Mallotus villosus) is an important forage fish in northern latitudes. The effect of the individual biological variability on the target strength (TS) at various acoustic frequencies was investigated from a sample collected in the St. Lawrence estuary. The geometric properties of the fish and its swimbladder were measured from radiographs obtained from 45 anesthetized fish, from 12- to 16-cm total length. The data were input to a backscattering model exploring the effect of fish shape on TS as a function of acoustic frequency, length, and tilt angle. The swimbladder had similar cross sections in both lateral and dorsal views. It represented 5.5% (s.d. 1.1%) of lateral body cross section and 8.2% (s.d. 1.8%) of the dorsal body cross section. The swimbladder cross section was related to the fish total length but the variation around the mean for a given length was ±40%. This large variability is equivalent to the change in cross section between tilt angles of 0 and 90 deg for an average fish. The variability in shape parameters is paralleled with changes in the modeled backscatter patterns. The TS versus frequency relation exhibits substantial peaks and troughs, notably in the range of acoustic frequencies commonly used in fisheries acoustics (∼38–200 kHz).
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".