Explorer AUV missions in coastal Newfoundland
Bibliographic record
Abstract
The Marine Environmental Lab for Intelligent Vehicles (MERLIN Lab) at Memorial University of Newfoundland (MUN) operates a survey class autonomous underwater vehicle (AUV) available for scientific research within a wide range of disciplines. The MUN Explorer is 4.5 meters in length, 0.69 meters in diameter, weighs 650 kg and displaces 660 kg. This International Submarine Engineering Ltd. (ISE) Explorer class vehicle has the capacity to handle 200 kg of scientific payload. With a range of up to 100 km at speeds of up to 2.5 m/s and depths to 3000 metres, the vehicle is ideal for environmental surveys where bathymetric and mapping sonar, physical and chemicals sensors, cameras and acoustic devices are carried. The paper focuses on the capabilities of the MUN Explorer AUV and plans to build collaborative projects. Data will be presented on vehicle performance during habitat mapping in coastal Newfoundland. Habitat mapping was conducted with Fisheries and Oceans Canada by using a single frequency acoustic system adapted to the AUV. The aim is to evaluate the potential to cost effectively classify seabed habitats as well as to monitor fish and zooplankton abundance and distributions in association with these habitats. The work detailed in this paper concerns the preliminary evaluation of the AUV as a research tool in this context.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".