Filling a data gap – Lake whitefish (<i>Coregonus clupeaformis</i>) index netting in the North Channel of Lake Huron
Bibliographic record
Abstract
The Anishinabek/Ontario Fisheries Resource Centre collaborated with the First Nation communities along the North Channel of Lake Huron – Aundeck-Omni-Kaning, Mississauga, Sagamok Anishnawbek, Serpent River and Wikwemikong Unceded – on a 5-year lake whitefish (Coregonus clupeaformis) index netting project. The impetus for this undertaking was concern that adequate information was not available for the derivation of the commercial catch quotas by the Ontario Ministry of Natural Resources. Traditional First Nation fishing waters were sampled from 2000 to 2004 using the Ontario Ministry of Natural Resources index netting methodology. A total of 2,760 lake whitefish were caught in 468 net sets, representing up to 17 year classes. The catch-per-unit-effort, as well as the number of year classes represented in the catch, was greater in Aundeck-Omni-Kaning than in the other four areas in the North Channel. The size and age at which 50% of lake whitefish are mature, ranged from 350 mm to 520 mm and 3 to 5 years, respectively. The data gathered from this study augmented the Ontario Ministry of Natural Resources biological catch data and was used in their statistical catch-at-age models for the derivation of lake whitefish commercial catch quotas in the North Channel.
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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 | 0.001 |
| 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 | 0.001 |
| 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".