Optimized Application of Multibeam Bathymetry Technology in Seafloor Surveys
Bibliographic record
Abstract
This study focuses on optimizing multibeam bathymetry technology, applying it to underwater terrain measurement, achieving a transition from point-to-line measurement, and minimizing the measurement path. Using the sine theorem and slope cosine theorem, a mathematical model for coverage width in the presence of slopes is established. The study calculates the seawater depth, coverage width, and overlap rate with the previous measurement line at various positions along the measurement line from the center point, with a distance of 800m resulting in a seawater depth of 49.05m and a coverage width of 170.27m. Subsequently, multiple β angles are selected to quantitatively analyze the impact of different angles on the measurement. Combining the established coverage width model, a mathematical model for coverage width at a certain distance from the center of the maritime area is developed for different β angles. The conclusion is drawn that at a β angle of 180 degrees, the farthest point from the center of the maritime area has the minimum coverage width of 63.03m, while at a β angle of 0 degrees, the farthest point has the maximum coverage width of 770.07m.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".