Isolation of<i>Bacteroides</i>from fish and human fecal samples for identification of unique molecular markers
Bibliographic record
Abstract
Bacteroides molecular markers have been used to identify human fecal contamination in natural waters, but recent work in our laboratory confirmed cross-amplification of several human-specific Bacteroides spp. assays with fecal DNA from fish. For identification of unique molecular markers, Bacteroides from human (n = 4) and fish (n = 7) fecal samples were cultured and their identities were further confirmed using Rapid ID 32A API strips. The 16S rDNA from multiple isolates from each sample was PCR amplified, cloned, and sequenced to identify unique markers for development of more stringent human-specific assays. In human feces, Bacteroides vulgatus was the dominant species (75% of isolates), whereas in tilapia feces, Bacteroides eggerthii was dominant (66%). Bacteroides from grass carp, channel catfish, and blue catfish may include Bacteroides uniformis, Bacteroides ovatus, or Bacteroides stercoris. Phylogenic analyses of the 16S rRNA gene sequences showed distinct Bacteroides groupings from each fish species, while human sequences clustered with known B. vulgatus. None of the fish isolates showed significant similarity to Bacteroides sequences currently deposited in NCBI (National Center for Biotechnology Information). This study expands the current sequence database of cultured fish Bacteroides. Such data are essential for identification of unique molecular markers in human Bacteroides that can be utilized in differentiating fish and human fecal contamination in water samples.
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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 | 0.001 |
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".