Science Response : recovery potential assessment terms of reference elements for Sei Whale (Atlantic population)
Bibliographic record
Abstract
In May 2019 the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) assessed the Atlantic Population of Sei Whale (hereafter simply referred to as “Sei Whale” in this document) as Endangered, primarily due to a possible population decline of greater than fifty percent over the past three generations from past whaling and, more recently, due to other threats. The Species at Risk Program in Newfoundland and Labrador Region requested that DFO Science provide Science Advice, via a Canadian Science Advisory Secretariat (CSAS) process, regarding the following four elements of a Recovery Potential Assessment (RPA) for the Sei Whale to help inform the listing decision for the species: 1. Element 8: Assess and prioritize the threats to the survival and recovery of the Sei Whale. 2. Element 12: Propose candidate abundance and distribution target(s) for recovery. 3. Element 16: Develop an inventory of feasible mitigation measures and reasonable alternatives to the activities that are threats to the species and its habitat. 4. Element 22: Evaluate maximum human-induced mortality and habitat destruction that the species can sustain without jeopardizing its survival or recovery. This Science Response Report results from the National Science Response Process ending February 23, 2022, on the Recovery Potential Assessment – Sei Whale (Balaenoptera borealis), Atlantic population.
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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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.032 | 0.028 |
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".