High Resolution Seabed Sub-Bottom Profiler for AUV
Bibliographic record
Abstract
Memorial University of Newfoundland (Memorial) is undertaking a novel and exciting area of interdisciplinary research and development related to Autonomous Underwater Vehicles (AUV). AUVs are an untethered, unmanned technology that enables a broad array of research, especially in hazardous underwater environments, that cannot be achieved by other means. In spring 2010, Memorial University commenced design work on a project that aims to provide a means to conduct high-resolution sub-bottom seabed surveys in water depths up to 1000 m (3281 ft), using a new imaging sub-bottom profiler technology with a 10 cm (3.9 in) resolution that has never been deployed on an AUV. The purpose of this project is to integrate a long-array sub-bottom profiler developed by PanGeo Subsea Inc. of Canada, into Memorial’s Explorer AUV by building a new vehicle section that resembles a thick airplane wing with a span of 3.5 m (11.5 ft). Memorial University is working to make the new equipment easily adaptable and removable from the Explorer AUV while in operation. The Explorer AUV equipped with this new sub-bottom profiler capability will be operational in 2012. In this paper, the underlying design criteria and challenges are discussed. A preliminary concept design is described and coarsely evaluated for technical feasibility.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".