Spoligotype analysis of<i>Mycobacterium bovis</i>isolates from Northern México
Bibliographic record
Abstract
Bovine tuberculosis is still rife in Latin America, producing huge economic losses. There are very few studies of the way this disease is spread through this geographical region, particularly in countries that border those that are almost free of Mycobacterium bovis. In this work, we have analyzed the spacer oligonucleotide typing (spoligotype) patterns of M. bovis isolates from cattle at Ciudad Juárez, a Mexican city close to El Paso, Texas. Fifty-eight M. bovis isolates collected from a herd in Northern Mexico were studied by spoligotyping. Nine spoligotype patterns were observed in total. Two were predominant (SB0121 and SB0140) and accounted for 50% and 14% of the isolates, respectively. Six patterns were found to be already described in an international M. bovis spoligotype database, while the other three (SB0985, SB0986, and SB0987) were novel. Interestingly, none of the isolates corresponded to any other Mexican pattern previously reported. This is the first spoligotype analysis of M. bovis strains from a border city between Mexico and the United States. The necessity for further studies to formulate a better identification of M. bovis strains within, and its dissemination between, the two countries is discussed.
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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 | 0.000 | 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 | 0.000 |
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".