Helminth communities of yellow perch (<i>Perca flavescens</i> (Mitchill)): determinants of pattern
Bibliographic record
Abstract
Twenty-eight parasite species were recorded from 504 yellow perch (Perca flavescens) collected from Dauphin Lake and Beaufort Lake, Manitoba, and Lake Winnebago, Green Bay, and Lake Michigan, Wisconsin. Four parasite species, Diplostomum spp., Urocleidus adspectus, Proteocephalus pearsei, and Raphidascaris acus, occurred in perch from all localities. Infracommunities and component communities were low in richness. The Dauphin Lake and Beaufort Lake samples had the richest parasite communities, while those in the Green Bay and Lake Michigan samples were the least rich. The effect of host size and age on parasite community structure was equivocal. A positive association between P. pearsei and Bothriocephalus cuspidatus and more multispecies infracommunities than expected provide evidence of nonrandom associations in the Manitoba samples, while the Wisconsin infracommunities were random associations. Significant infracommunity nestedness in all samples indicated nonrandom community organization and structure. Parasite faunas were richer in samples with complex invertebrate communities than in samples with complex fish communities. The trophic status of the aquatic system indirectly affected the parasite communities by limiting the variety of potential intermediate hosts. Predictions regarding relationships between parasite community structure and lake trophic status were not supported. We show that predictable patterns at the fine-scale local level of the parasite infracommunity and component communities of perch are best explained by a rich invertebrate community upon which the host feeds.
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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".