Typing of Mycobacterium avium Subspecies paratuberculosis Isolates from Newfoundland Using Fragment Analysis
Bibliographic record
Abstract
Short Sequence Repeat (SSR) typing of Mycobacterium avium subspecies paratuberculosis (Map) isolates is one of the most commonly used method for genotyping this pathogen. Currently used techniques have challenges in analyzing mononucleotide repeats >15 bp, which include some of the Map SSRs. Fragment analysis is a relatively simple technique, which can accurately measure the size of DNA fragments and can be used to calculate the repeat length of the target SSR loci. In the present study, fragment analysis was used to analyze 4 Map SSR loci known to provide sufficient discriminatory power to determine the relationship between Map isolates. Eighty-five Map isolates from 18 animals from the island of Newfoundland were successfully genotyped using fragment analysis. To the best of our knowledge, this is the first report on Map SSR diversity from Newfoundland dairy farms. Previously unreported Map SSR-types or combinations were also identified during the course of the described work. In addition, multiple Map SSR-types were isolated from a single animal in many cases, which is not a common finding.
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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 | 0.000 |
| 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 | 0.000 |
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".