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Record W3197262847 · doi:10.31083/0003-925x-64-103

Influence of quarter-individual milking in a conventional milking parlor on milk constituents of dairy cows

2013· article· en· W3197262847 on OpenAlexaboutno aff
Anika Müller, Sandra Rose-Meierhöfer, Christian Ammon, Sabrina Elsholz, Reiner Brunsch

Bibliographic record

VenueArchiv für Lebensmittelhygiene · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsnot available
FundersBundesamt für Landwirtschaft
KeywordsMilkingQuarter (Canadian coin)Automatic milkingAnimal scienceDairy cattleFood scienceAgricultural scienceBiologyLactationIce calvingGeography

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.250
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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