Diurnal variation in acoustic densities: why do we see less in the dark?
Bibliographic record
Abstract
Diurnal fluctuations in total integrated echo abundance and in vertical density profiles were examined using data from the Norwegian combined acoustic and bottom-trawl survey for demersal fish during winter in the Barents Sea. The total echo abundance was about 40%50% higher at day than at night. An unknown amount of fish was lost close to the seabed in the acoustic dead zone, but the systematic changes in the near-bottom vertical density profiles did not indicate that migration in and out of the dead zone was the major reason for the large diurnal differences in echo abundance. A more plausible explanation could be that diurnal changes in fish behaviour affect the mean acoustic target strength. Based on the present study, we recommend that the time series of acoustic surveys should be re analysed, taking the diurnal bias into account. Any comparison of the fish densities indicated by trawl and acoustic surveys will suffer if this bias is not corrected. We believe that model development utilizing this type of information is crucial for future ecosystem-based monitoring.
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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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".