The Ecology of Body Size and Depth Use by Bloater (<i>Coregonus hoyi</i>Gill) in the Laurentian Great Lakes: Patterns and Hypotheses
Bibliographic record
Abstract
Deepwater ciscoes (genus Coregonus, subgenus Leucichthys) radiated into six phenotypes that occupy different depths in the Great Lakes, based upon body size and lipid content. Large, lipid-dense ciscoes occupy greater depths than small, lean ciscoes. This relationship is observed between adults and juveniles of the most prevalent deepwater cisco, the bloater (C. hoyi Gill). Lipid-dense adult bloaters are restricted to the hypolimnion, whereas lean juveniles are found primarily in the epilimnion. This article critically reviews, synthesizes, and provides hypotheses from the literature on the ecology of body size and depth use of bloater. Factors influencing depth use in bloater are categorized by Fry's (1971) environmental factors. The case is made for two parsimonious hypotheses to explain the depth distribution by body size of bloater: (1) the optimal foraging-antipredation (OFA) hypothesis, and (2) the mass-specific metabolism hypothesis. The OFA hypothesis relates abundance of piscivores with abundance and extent of diel vertical migration of bloater. The mass-specific metabolism hypothesis relates body size to density-dependent growth, metabolism, swimming activity and hence depth distribution of bloater. Follow-up hypotheses and predictions are presented and may broaden our understanding of trophic ecology and adaptive radiation of deepwater ciscoes in the Great Lakes.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".