Single beam echosounding: Considerations of depth and seabed slope
Bibliographic record
Abstract
The topic of depth compensation of single beam echo time series for seabed classification is fairly well studied. The effect of seabed slope has not been publicized. In applications for seabed classification, seabed slope is observed to be associated with classification inaccuracy and failure. In cases of higher slope, single beam bathymetry also becomes inaccurate. A survey of 2 fjords with extreme variation in slope is presented as a representative example and testing bed for investigating slope. The direct effect on seabed echoes is investigated and explained in reference to a simple model of beam-echo geometry. Survey bathymetry is compensated for slope; inaccuracies of up to 5% of depth are corrected, however bottom picking accuracy is diminished in areas of slope and cannot be improved. Surveys of a gas hydrate site and a river will also be presented as applications of these ideas. Early results from BORIS model studies of methods for compensation of slope and depth may also be presented.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".