The role of the bovine respiratory bacterial microbiota in health and disease
Bibliographic record
Abstract
Increased antimicrobial resistance in bovine respiratory bacterial pathogens poses a threat to the effective control and prevention of bovine respiratory disease (BRD). As part of continued efforts to develop antimicrobial alternatives to mitigate BRD, the microbial community residing within the respiratory tract of feedlot cattle has been increasingly studied using next-generation sequencing technologies. The mucosal surfaces of upper and lower respiratory tracts of cattle are colonized by a diverse and dynamic microbiota encompassing commensal, symbiotic, and pathogenic bacteria. While a direct causal relationship between respiratory microbiota and the development of BRD in feedlot cattle has not been fully elucidated, increasing evidence suggests that the microbiota contributes to respiratory health by providing colonization resistance against pathogens and maintaining homeostasis. Certain management practices such as weaning, transportation, feed transition, and antibiotic application can disrupt the respiratory microbiota, potentially altering pathogen colonization. Microbiota-based approaches, including bacterial therapeutics that target restoring the normal respiratory microbiota, may provide new methods for mitigating BRD in feedlot cattle in place of antibiotics. In addition, the distinct bacterial respiratory microbial communities observed in BRD-affected and healthy feedlot cattle may allow for future application of microbiota-based techniques used in the diagnosis of BRD.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".