Influence of quarter-individual milking in a conventional milking parlor on milk constituents of dairy cows
Bibliographic record
Abstract
To evaluate the effect of milking with single tube guidance (MULTI) in comparison with conventional milking clusters (CON), various milk parameters were analyzed in foremilk samples. The two milking systems had the following technical configurations: milking vacuum was set to 37 kPa (MULTI) and 41 kPa (CON), respectively. Pulsation ratios were 65:35 (MULTI) and 60:40 (CON); both milking systems worked with a pulsation rate of 60 cycles/min. Furthermore, MULTI allowed periodic air inlet into the pulsation chamber of the teat cups (BioMilker®) and used sequential pulsation. For the experiment, 57 German Holstein cows were randomly allocated to two groups (group 1: exclusively milked with MULTI, 28 cows; group 2: exclusively milked with CON, 29 cows). Foremilk samples were analyzed for fat, lactose, electrical conductivity (EC) and somatic cell count (SCC). Milking system could not be found to have a significant effect on the analyzed parameters. The fixed effect trial week had a significant effect on all examined traits. Furthermore, parity showed a sigificant impact on most investigated traits with exception of EC, and the covariable day in milk (DIM) showed a significant impact on fat, lactose and EC. In summary, milking with single guided milk tubes did not change the percentage of milk components (fat, lactose) and the level of milk characteristics (EC, SCC), compared with conventional milking.
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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 | 0.000 | 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".