Prevalence of lip neoplasms of white sucker (<i>Catostomus commersoni</i>) in the St. Lawrence River basin
Bibliographic record
Abstract
The prevalence of lip neoplasms in populations of white sucker (Catostomus commersoni) was compared among five locations in the St. Lawrence River basin, Quebec, Canada. One site in the St. Lawrence River was monitored from May 15 to October 30 for two consecutive years (1994-1995) to study the seasonal variations in the prevalence of lip neoplasms. Other sites were sampled within a few days in October 1995 or May 1996. Lesions were found in fish from four of the five sites. The prevalence at each site varied from 0 to 41.6% and, as found in the Great Lakes, was highest in fish populations from urbanized/industrialized sites. Lip neoplams were detected almost only in fish >350 mm (total length). The prevalence was slightly higher in fish captured in the spring, but the low sample size did not permit statistical detection of this seasonal variation. There was a significant positive correlation (Spearman rs = 0.83) between fish length and the prevalence and size of lesions. The prevalence was similar between sexes, and the condition factor was significantly lower in fish with papillomas from one site only. In future studies, fish size and season of capture should be taken into account to compare the prevalence of lip neoplasms of white sucker from different sites.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".