Time-lapse imagery of a highly active submarine channel and its implications for seafloor geohazards
Bibliographic record
Abstract
National Oceanography Centre (1); Ocean and earth Sciences, University of Southampton (2); Departments of geography and Earth Sciences, Durham University (3); Department of Geoscience, University of Calgary (4); Natural Resources Canada (5); Energy and Environment Institute, University of Hull (6); Center for Coastal Ocean Mapping, University of New Hampshire (7) <br> <br> With increasing energy and communication demands, and recent advances in technology, seafloor infrastructure becomes more abundant. For instance, a global network of seafloor cables transfers 99% of digital data traffic and breakage of those cables can disrupt financial trading, communications and internet connections. Cables that cross submarine channels are particularly vulnerable to breaks by powerful avalanches of sediment, called turbidity currents. Assessing geohazards in these systems is difficult due to limited mapping or monitoring. Submarine canyons and channels cannot be monitored using satellites, hence we rely on offshore expeditions to these often-remote systems and use acoustic instruments like multibeam echosounders to map them.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".