Assessment of NAFO subdiv. 3Ps thorny skate
Bibliographic record
Abstract
Bottom temperatures in NAFO Subdiv. 3Ps remained above normal between 2009 and 2019, but no data are available for 2020. Zooplankton data were also unavailable for 2019 and 2020. Satellite imagery indicated that the timing and magnitude of the spring phytoplankton bloom were normal in 2020, after two consecutive years of early onset and above-normal production. Ongoing warming trends, together with an increased dominance of warm water fishes, indicate that this ecosystem continues to experience structural changes. Thorny Skate in Subdiv. 3Ps and adjacent Div. 3LNO are considered to constitute a single stock, which is managed by Canada in Subdiv. 3Ps and by NAFO in Div. 3LNO. Life history characteristics of Thorny Skate result in low intrinsic rates of population growth; thereby leading to low resilience to fishing mortality. In Subdiv. 3Ps, reported landings by Canada and France totaled 1,059 t in 2018, and 969 t in 2019, approximately double the previous six year average catch (497 t over 2012–2017). The Canadian DFO research survey abundance index for Subdiv. 3Ps was relatively stable from 1993–2019, while the survey biomass index indicated a gradually increasing trend. Similar trends were observed in Div. 3LNO. There was no spring survey in 2020. The relative estimate of fishing mortality for Thorny Skate in Subdiv. 3Ps has been below the long-term average (1996–2019) since 2010. Relative fishing mortality in Div. 3LNO also remains low. In Subdiv. 3Ps, the abundance of Thorny Skates ≤21 cm in total length has been below average during 2018–2019. Overall, the stock recruitment index for the entire stock area in Subdiv.3Ps and Div. 3LNO has also fluctuated without trend, but has been below the long term average over 2018-2019. The Thorny Skate stock in Subdiv. 3Ps and Div. 3LNO is currently above Blim. The probability that the current biomass is above Blim is >95%. The stock biomass has been generally increasing since the mid-1990s, indicating that the stock has been able to sustain the range of catches over this period.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".