Analysis of Haddock (<i>Melanogrammus aeglefinus</i>) sounds recorded in the Northwest Atlantic
Bibliographic record
Abstract
Haddock (Melanogrammus aeglefinus) are present on both sides of the North Atlantic. Their distribution in the Northwest Atlantic ranges from Greenland to North Carolina. They are an important food resource that needs to be closely monitored to ensure a sustainable fishery. Research studies have reported that both male and female haddock produce sounds during courtship and spawning. These sounds can be used to monitor spawning activities non-intrusively and at large scale. The objective of this paper is to analyse the spatial and temporal occurrence of Haddock sounds in the Gulf of Maine. Passive acoustic data were collected in 2003, 2004, 2006, and 2007 in areas known to contain spawning haddock. To analyze the large amount of data collected, an automated haddock sound detector was developed based on a measure of kurtosis and the Dynamic Time Warping algorithm. The detector was trained using the 2006 and 2007 data and its performance was quantified and optimized by comparing detection results with manually annotated Haddock sounds. The detector was then used to analyze data collected in 2003 and 2004. Results provide information on the temporal and spatial distributions of courtship and spawning sounds.
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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 | 0.000 |
| 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 | 0.000 | 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".