Selenium levels in Lesser Scaup ( Aythya affinis ) experimentally infected with introduced trematodes
Bibliographic record
Abstract
Lesser Scaup (Aythya affinis) have declined nearly 60% over the past five decades and remain below the continental population objective. Since the early 2000s, epizootic intestinal trematodiasis caused by introduced trematodes (Cyathocotyle bushiensis, Sphaeridiotrema globulus, and Sphaeridiotrema pseudoglobulus) have been documented as a proximate cause of scaup mortalities while the consequences of sub-lethal infections on individuals remain unknown. Trace elements including lead, cadmium, and selenium may also have deleterious effects on scaup by reducing the immune system function, but cumulative effects in combination with trematodiasis have not been previously investigated. We evaluated the potential interactive relationships of heavy metal contaminants and trematode infections in wild-caught and captive-reared scaup in captivity. Across three experimental trials, 60 scaup received a single, sub-lethal dose of metacercariae and were subsequently assessed for hepatic lead, cadmium, and selenium concentrations relative to gross lesions and trematode counts at necropsy. No relationship was detected between lead or cadmium liver concentrations and trematode infections. We found a negative relationship between trematode infections and selenium liver concentrations. Selenium is an essential nutrient for animals specifically to protect the host body from cellular damage during an immune response. Trematodiasis in free ranging scaup may contribute to selenium deficiencies, which could deleteriously affect survival and body condition. Selenium deficiency from trematodiasis could be a contributing factor to health of Lesser Scaup, but we did not find interactive effects across contaminants and trematodiasis that would suggest substantial population-level issues.
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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) | 0.001 | 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 | 0.001 |
| 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".