Passive acoustic monitoring of haddock in the Gulf of Maine
Bibliographic record
Abstract
We have conducted several studies of haddock sounds in the Gulf of Maine (GOM) with mixed results. An analysis of an archival recording from captive haddock brood stock made in 1970 found that the “spawning rumble” sound occurred variously at the end of short thump trains, in the middle of thump trains, or in isolation. Interestingly, haddock were silent while spawning when we attempted to record sounds in the same facility in March 2000, suggesting that sound production may be negatively affected by chronic noise. Haddock sounds were absent in ROV and tethered instrument surveys in the summer and fall of 2001-2002. During 2006-2007, we deployed bottom mounted recorders while conducting long-line surveys of haddock spawning condition. Surprisingly few haddock sounds were detected and there was no correlation with spawning activity despite recording in highly active spawning areas. Haddock sounds consisted of isolated knocks, which were difficult to distinguish from thumps of unknown origin. We are now applying autodetection algorithms tuned to these data sets to extensive recordings made on the fishing grounds in 2003-2004. Our observations suggest that GOM haddock spawn in small isolated groups within a larger spawning area and their sounds are detectable only over short distances.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".