Microbiological quality of bulk tank raw milk in Prince Edward Island dairy herds
Bibliographic record
Abstract
The objectives of this study were to evaluate microbiological quality of bulk tank milk in Prince Edward Island, to evaluate correlation among milk quality criteria, and to determine seasonal effects on milk quality parameters. Bulk tank raw milk quality was evaluated on all Prince Edward Island dairy herds (n = 235) over a 2-yr period (March 2005 to March 2007). Biweekly total aerobic (TAC), preliminary incubation (PIC), laboratory pasteurization, and coliform (CC) counts were determined using a Petrifilm culture system. Additionally, bulk tank somatic cell count was determined weekly. The mean and median values were 12.8 x 10(3) and 4.9 x 10(3) cfu/mL for TAC, 29.6 x 10(3) and 13 x 10(3) cfu/mL for PIC, 87 and 12 cfu/mL for laboratory pasteurization count, 21 and 5 cfu/mL for CC, and 218 x 10(3) and 187 x 10(3) cells/mL for somatic cell count. There was moderate correlation (0.57) between TAC and PIC. All other correlation coefficients were low (<0.26). Correlation results suggest that a single quality parameter could not predict others used in this study. Seasonal data indicate that 1) in general, all counts tended to be low in winter, 2) the CC and somatic cell count were always high in summer, and 3) TAC tended to be high during summer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".