Morphometry, Growth, and Condition of Hatchery-Reared Cisco (<i>Coregonus artedi</i>) and Bloater (<i>Coregonus hoyi</i>)
Bibliographic record
Abstract
The re-introduction of native species that have been extirpated or in low abundance in the Great Lakes has been a binational initiative between the United States and Canadian governments. Recently, new management programs have been underway that use current hatchery facilities for the restoration of native forage fishes in Lake Ontario. These species include Bloater (Coregonus hoyi), which has been extirpated from Lake Ontario for approximately four decades, and Cisco (C. artedi), which exists at a fraction of its former abundance. We assessed morphometrics, length-weight relationships, and condition factors during early life development for eight cohorts of Cisco and Bloater reared from 2012-2019. Weekly samples for Cisco and Bloater were measured from hatch until release (29-45 weeks, 133-1,002 samples annually). Head width, gape, mandible length, and mouth height metrics were all larger for Cisco than Bloater at any given size but increased at similar rates for both species. Average condition factors for Cisco and Bloater were 0.54317 and 0.55892, respectively. This information may also improve field identification of these species, helping managers evaluate the relative success of different release strategies for rehabilitation of populations of these native 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 | 0.001 | 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) | 0.002 | 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".