An assessment of Sea Scallop (Placopecten magellanicus) on St. Pierre Bank in 2019
Bibliographic record
Abstract
Populations of Sea Scallop (Placopecten magellanicus) on St. Pierre Bank are mainly found in three beds (North, Middle, and South beds) at depths of 40–100 m. They are usually found on hard bottom with variable substrate composition, consisting largely of sand, gravel, shell fragments, and stones. The Sea and Iceland Scallop distributions overlap to varying degrees with complete overlap in the Middle bed, and a high degree of overlap in the North bed. A large area in the southern portion of the South bed, with a sandy substrate, is inhabited by only Sea Scallop. The directed fishery for Sea Scallop started on the St. Pierre Bank in the late 1970s. Prior to 2006, the fishery was managed by total allowable catch (TAC), and meat count regulations were applied to the offshore fleet, but not to the inshore fleet. In 2006, following the recommendations of the Hooley Report, specific fishing areas and TACs were applied to each fleet. From 2006 to 2015, the offshore fleet did not fish on the St. Pierre Bank but began fishing again in 2016. In contrast, fishing has been consistently prosecuted in the North bed by the Newfoundland and Labrador (NL) inshore fleet since 2006. From 2016 to 2019 landings averaged 720 t, round weight in the North bed, and 90 t, meat weight in the Middle and South beds. A Fisheries and Oceans Canada (DFO) survey in September 2019 resulted in a minimum dredgeable biomass (MDB) estimate of 12,725 t, round weight. This point estimate is associated with high variability and a subsequent high level of uncertainty. The stock in the North bed is currently dominated by a modal group of scallop 75 mm, while in the Middle and South beds the modal group is 120 mm and 130 mm, respectively. The natural mortality index for Sea Scallop has decreased from 0.13 in 2015 to 0.02 in 2019, similar to levels observed from 2003 to 2006. The abundance of small scallop in the North bed indicate favourable prospects for the fishery in the near future.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".