Genetic monitoring program for beluga (Delphinapterus leucas) harvested in the Nunavik and Nunavut (Belcher Islands) regions
Bibliographic record
Abstract
A genetic monitoring program for beluga harvested in Nunavik and Nunavut-Belcher Islands management units is ongoing at Fisheries and Oceans Canada (DFO). With this document, we aim to increase transparency in methods used and enable reproducible results in other laboratories analyzing similar tissues. This document presents 1) the extent of the tissue collection from Nunavik, 2) an improved haplotyping method, 3) an improved sex determination method, and 4) results for individual genetic assignment to the populations/stocks in the Hudson Bay-Strait Complex. Our results for the individual genetic assignment show that the updated genetic definition of the beluga summering in the distribution of the Eastern Hudson Bay designatable unit, recently identified as the Belcher Islands and Eastern Hudson Bay (BEL-EHB) stock, has led to increased uncertainty associated with this method. The high uncertainty makes this approach unsuitable for providing seasonal estimates of the number of BEL-EHB animals harvested in Nunavik and Nunavut-Belcher Islands. The alternative approach for annual updates of populations or stocks proportions harvested in Nunavik and Nunavut-Belcher Islands management areas is discussed.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".