The Future of North Atlantic Right Whales and Fishing and Shipping Interactions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.000 | 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) | 0.000 | 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 it