When fish meet a trawling vessel: examining the behaviour of gadoids using a free-floating buoy and acoustic split-beam tracking
Bibliographic record
Abstract
The reaction of individual gadoids to a bottom-trawling vessel has been observed in situ in the Barents Sea using a free-floating buoy and acoustic target-tracking methods. More than 20 000 tracks were analysed in terms of velocity changes in vertical, athwarthship, and alongship direction relative to the vessel, the warps, and the trawl, respectively. The fish starts diving about 15 min before vessel passing. This coincides with the time the trawl is running and not with the gradual increase in vessel noise caused by the approaching vessel. The change in horizontal movement is more gradual and is directed away from the vessel in the alongship direction, but towards the vessel in the athwarthship direction. The strongest and sharpest response is related to the trawl warps. A strong herding in front of the warps is seen. Closer to the bottom, an athwarthship herding reaction is seen away from the trawl doors or possibly the lower parts of the warps. There were only minor differences when grouping the tracks according to light level, fish size, and fish density.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".