Analysis of underwater benthic images obtained from ROV ROPOS cruise in the Cape Breton Trough in 2017
Bibliographic record
Abstract
A collaborative scientific expedition between Fisheries and Oceans Canada (DFO) and Oceana Canada was undertaken in August 2017 to explore the benthic ecosystems in the Cape Breton Trough (CBT), an area within the Gulf of St. Lawrence that is not well-known as trawl sampling is difficult. The CBT, which lies within the boundaries of the Western Cape Breton Ecologically and Biologically Significant Area (EBSA), was explored using a remotely operated underwater vehicle, ROPOS (Remotely Operated Platform for Ocean Science). Benthic images from underwater video recorded along transects were annotated to characterize species and substrate type. Sediment and water samples were collected for biogeochemical analysis. Overall, the objectives were to describe communities of epibenthic species, collect samples, and identify potential habitat sites for the Atlantic wolffish (Anarhichas lupus) which is currently listed as a species of special concern in the Species at Risk Act (SARA) Public Registry. The key findings were describing taxa density along four transects, the identification of 13 sponge taxa from sampled material, the observation of areas with dense sea anemone aggregations, and the identification of habitats suitable for wolffish, although no individuals were seen during the mission. This work increases our knowledge of the benthic fauna and communities of the Cape Breton Trough area.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".