Comparative study of behavioural and milking traits in cows milked with a conventional or individual quarter milking system (Multilactor®) and with different milking persons
Bibliographic record
Abstract
The aim of this study was to investigate the influence of a new type of milking system on the behaviour of cows during milking by comparing a conventional milking system (CON) with an individual quarter milking system (MUL), MultiLactor®. Sixty-eight dairy cows were observed during their milking times (32 cows in CON, 36 cows in MUL) using video recordings to analyse their behavioural traits. The udder preparation duration, milking duration and milk yield were also evaluated. No significant differences were found between the CON and the MUL regarding cows' head posture (P=0.38), body posture (P=0.85), number of steps (P=0.08) and number of kicks (P=0.56). However, the milk yield was lower (P=0.02), just as the udder preparation duration (P<0.01) and milking duration (P=0.01) were shorter in the CON compared to the MUL. In addition, in regard to the milking person, differences were displayed in the head posture of the milked cows, kick-off or loss of teat cup or milking cluster, and frequency of udder preparation. In conclusion, the investigated milking systems did not markedly influence the behaviour of dairy cows; however, udder preparation duration, milking duration and milk yield were significantly greater for the MUL than for the CON. However, the milking person appears to have a greater impact on the behaviour of the cows than the milking system. © 2017 Sciendo. All Rights Reserved.
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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".