Associations of lobsters (Homarus americanus) off southwestern Nova Scotia with bottom type from images and geophysical maps
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.Images from an underwater towed vehicle (Towcam) are used to evaluate habitat associations of lobsters (Homarus americanus) along with crabs (Cancer sp) and scallops (Placopecten magellanicus). Images were obtained in Oct. 2006 in an area off southwest Nova Scotia in an area with productive lobster and scallop fisheries. Lobsters were observed in 4% of the 2080 images, crabs in 7% and scallops in 40%. On sand, gravel and cobble bottoms lobsters were readily seen. On rougher bottoms with boulders, some lobsters were still evident either in the open or partially hidden in shelters. Models of animal presence with bottom type were evaluated with categories based on (i) sediment size from images and (ii) a map of bottom type based on geophysical characteristics. Significant relationships were evident with both types of bottom categorizations. While each geophysical category had a range of sediment sizes, they had unique mixes of sediment sizes which appear to explain the particular associations between the 3 species and bottom type. There is good potential for using underwater imaging to develop surveys for indicators of lobster abundance and stratification by bottom type should be incorporated
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 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 | 0.000 | 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) | 0.004 | 0.001 |
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".