The Future of North Atlantic Right Whales and Fishing and Shipping Interactions
Bibliographic record
Abstract
Abstract Despite almost a century protected from whaling, the North Atlantic right whale remains endangered. This species grew from 292 individuals in 1992 to 482 individuals in 2010, but the decline since then has been precipitous; to 336 in 2020, and evidence suggests it continues to fall. Entanglements in rope and collisions by ocean-going vessels are the two human activities attributable to all known post-natal serious injuries and deaths. To consider if the ocean of our future will have North Atlantic right whales, first, the multiplicity of efforts underway to reduce harm to these animals are pre-sented. This includes spatial management measures for fishing and ship-ping in Canada and the United States, and the development and adoption of buoyless (i.e., on-demand, ropeless) fishing gear. Second, a brief reflec-tion is offered on the resilient traits and extraordinary recoveries this spe-cies has already shown. The conclusion of this discussion is that this is not a defeated species. It will recover if we stop harming them. Several important actions are necessary to accomplish this. These are simple to list but very challenging to put into practice, requiring, therefore, widespread and collec-tive willingness and support.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".