Discrimination of the endangered Atlantic Whitefish (Coregonus huntsmani Scott, 1987) larvae and juveniles
Bibliographic record
Abstract
Hasselman, D.J. and Bradford, R.G. 2012. Discrimination of the endangered Atlantic Whitefish (Coregonus huntsmani Scott, 1987) larvae and juveniles. Can. Tech. Rep. Fish. Aquat. Sci. 2993: iii + 24 p. Atlantic Whitefish (Coregonus huntsmani) are an endangered species endemic to Nova Scotia, Canada. Several actions identified in the Atlantic Whitefish recovery strategy require accurate identification of the species early life history stages. While criteria exists for the discrimination of adult specimens, no such criteria is available for larvae or juveniles. Using specimens obtained from the captive mating of wild caught adults, and those made available to this study, we conduct discriminant function analyses on phenetic characters, and incorporate speciesspecific pigmentation patterns to develop discrimination criteria for early life history stage Atlantic Whitefish, Lake Whitefish (C. clupeaformis), and Cisco (C. artedii). Quantifiable interspecific differences in the number of pre-anal myomeres, total myomeres, and anal fin ray counts, when combined with dorsal and ventral pigmentation patterns can be used to discriminate larval and juvenile specimens of Atlantic Whitefish, Lake Whitefish, and Cisco. The external characters identified as useful common reference points for the delineation of these three species could be extended to include additional coregonine species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".