Library-dependent and library-independent microbial source tracking to identify spatial variation in faecal contamination sources along a Lake Ontario beach (Ontario, Canada)
Bibliographic record
Abstract
Multiple microbial source tracking methods were applied to investigate spatial variation in faecal pollution sources impacting a 1.7 km freshwater beach on Lake Ontario (Canada). The highest E. coli concentrations measured in the study area were from interstitial sand pore water at Sunnyside Beach, reaching 2.6 x 10(6) CFU/100 ml. These E. coli concentrations exceeded those in the nearby Humber River and Black Creek, which are impacted by combined sewer overflows containing municipal wastewater and by stormwater conveying washoff from the urban area. Library-independent Bacteroidales HF183 analyses identified the more frequent occurrence of municipal wastewater contamination in the Humber River and at a Sunnyside Beach location closest to the mouth of the river. Library-dependent E. coli antibiotic resistance and rep-PCR DNA fingerprinting analyses identified the more frequent occurrence of bird faecal contamination at Sunnyside Beach locations away from the river mouth. These microbial source tracking results raise caution about managing beaches with multiple sources of contamination as a single entity without considering spatial variability in faecal pollution sources and the need for more localized beach management practices.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | medium |
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".