An adaptive, integrated “acoustic-trawl” survey design for Atlantic cod (Gadus morhua) with estimation of the acoustic and trawl dead zones
Bibliographic record
Abstract
Abstract The objectives of this study were to design an operationally efficient groundfish survey integrating both acoustic and trawl methodologies, to measure the changing vertical availability of cod to each method over 24 h and to compare cod-biomass estimates from the two methods within two experimental sub-regions. The two-phased sampling design involved (i) conducting an initial systematic acoustic survey to locate an area of high cod concentrations, (ii) using the acoustic-backscatter information to stratify the sub-regions into density strata for the allocation of trawl hauls, and (iii) conducting a second systematic acoustic survey at the same time as a random-stratified trawl survey. This protocol permitted the optimization of trawl sampling according to population density and the realization of simultaneous trawl and acoustic estimates for direct comparison. These cod showed extensive diel vertical migrations, which affected their availability to the trawl gear at night and the acoustic beam by day. An acoustic dead-zone correction was applied to the acoustic estimates, averaging 4–15% of the biomass for the night-time transects and 11–36% for the daytime transects. The detailed temporal acoustic monitoring of the vertical migrations permitted the quantification of the change in cod availability to the trawl gear. From 6% to 47% of cod were above the effective trawl height at night, while 0–10% of cod were in the “trawl dead zone” by day. Estimated cod densities were very similar between the two methods on a haul-by-haul basis after correcting each method for their respective inherent sampling biases. The total biomass estimates were also comparable between the two methods for one sub-region, although significantly higher from the trawl data for the other. The discrepancies were most likely a result of differences in the sampling density of the two methods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".