Choice of indicator organism and library size considerations for phenotypic microbial source tracking by FAME profiling
Bibliographic record
Abstract
The primary objective of this study was to investigate the effects of choice of the indicator organisms on the accuracy of classifying the fatty acid methyl ester (FAME) profiles of the known-source library isolates. First, a known-source library containing the FAME profiles of Enterococcus isolates cultured from six different possible sources of microbial pollution was developed. A total of 511 Enterococcus isolates were profiled: 120 isolates from sewage samples representing humans; 69 from dairy and cattle cow; 74 from chicken; 76 from swine; 94 from deer; and 78 from waterfowl. Classification of known-source Enterococcus isolates into their respective host categories resulted with a 66% average rate of correct classification (ARCC) in a six-way discriminant analysis (DA). The ARCC increased to 75% when the individual hosts were pooled into larger categories of human, livestock, and wildlife. The accuracy was 80% when isolates of human origin were discriminated against those of non-human origins. Recently, several studies reported the ARCCs for various classification schemes associated with total coliform (TC), fecal coliform (FC), and Escherichia coli of the known-source isolates. When the accuracy of classification of Enterococcus isolates was compared to those reported for TC, FC, and E. coli isolates, the lowest ARCCs were associated with classification of E. coli isolates, the only species level indicator organism among the four compared. It was found that the degree of discrimination increases as the indicator becomes more inclusive of bacteria from different genus. In addition, random cluster formation analysis indicates that known-source libraries with isolate numbers between 300 and 500 might be sufficient for MST by FAME.
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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: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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, 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".