Faecal indicators and pathogens in selected New Zealand waterfowl
Bibliographic record
Abstract
Abstract Freshly excreted droppings from Canada geese ( n =80), black swans ( n =80), ducks ( n =80) and gulls ( n =80) were collected from sites around New Zealand. The droppings were enumerated for Escherichia coli , enterococci and Salmonella spp., and for the presence/absence of Cryptosporidium spp. Overall prevalence of E . coli and enterococci in samples was 95% and 94%, respectively. Cryptosporidium spp. was detected in 2% of the samples, whereas no Salmonella spp. were detected in the survey. Preliminary estimates of daily microbial outputs suggest that ducks will produce the highest loadings of E . coli and enterococci per bird, whereas Canada geese will produce the highest loadings of Campylobacter spp. per bird. This study provides the first set of indicator and pathogen counts for one of the largest sources of diffuse faecal contamination of natural waters in New Zealand.
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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 | 0.000 | 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".