Raw sidescan and sub-bottom data acquired near-bottom in 2016 from the continental slope of the Canadian Beaufort Sea with MBARI mapping AUV on mission 20161001m1
Bibliographic record
Abstract
This raw sidescan and sub-bottom data set was collected with an Edgetech 2205 sonar/sub-bottom system on MBARI Mapping AUV mission 20161001m1 in 2016. The data files are in JSF format (compatible with MB-System as mbio format 132) and contain raw sidescan and sub-bottom data that has not been merged with navigation. The AUV survey mission was conducted during the 2016 CCGS Sir Wilfrid Laurier IOS cruise 2016-13 in the Beaufort Sea (Cruise Chief Scientist - Humfrey Melling, Department of Fisheries and Oceans Canada; project PI - Charlie Paull and investigators: Dr. David Caress and Eve Lundsten, MBARI). Data were acquired as part of a collaborative research project between MBARI, the Geological Survey of Canada, and Department of Fisheries and Oceans Canada to understand slope stability. Funding for the AUV mapping was provided from the David and Lucile Packard Foundation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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 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".