Sources of Clostridia in Raw Milk on Farms
Bibliographic record
Abstract
A PCR-denaturing gradient gel electrophoresis (DGGE) method was used to examine on-farm sources of Clostridium cluster I strains in four dairy farms over 2 years. Conventional microbiological analysis was used in parallel to monitor size of clostridial populations present in various components of the milk production chain (soil, forage, grass silage, maize silage, dry hay, and raw milk). PCR amplification with Clostridium cluster I-specific 16S rRNA gene primers followed by DGGE separation yielded a total of 47 operational taxonomic units (OTUs), which varied greatly with respect to frequency of occurrence. Some OTUs were found only in forage, and forage profiles differed according to farm location (southern or northern Québec). More clostridial contamination was found in maize silage than in grass silage. Milk represented a potential environment for certain OTUs. No OTU was milk specific, indicating that OTUs originated from other environments. Most (83%) of the OTUs detected in raw milk were also found in grass or maize silage. Milk DGGE profiles differed according to farm and sampling year and fit into two distinct categories. One milk profile category was characterized by the presence of a few dominant OTUs, the presence of which appeared to be more related to farm management than to feed contamination. OTUs were more varied in the second profile category. The identities of certain OTUs frequently found in milk were resolved by cloning and sequencing. Clostridium disporicum was identified as an important member of clostridial populations transmitted to milk. Clostridium tyrobutyricum was consistently found in milk and was widespread in the other farm environments examined.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".