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Influence of the Month on the Chemical Composition of Mediterranean Italian Buffalo Milk

2017· article· en· W2604113287 on OpenAlexvenueno aff
R. De Vivo, R. Napolano, L. Zicarelli

Bibliographic record

VenueJournal of Buffalo Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsnot available
Fundersnot available
KeywordsComposition (language)Mediterranean climateChemical compositionFood scienceBiologyChemistryArtEcologyLiterature

Abstract

fetched live from OpenAlex

It is known that the chemical composition of milk is influenced by several factors and the length of lactation plays a prominent role. In Italy, where the reproductive activity of the herd is aimed at the demand for milk from the market, the chemical composition is influenced not only by the adoption or otherwise by the out-breeding-mating-strategy (OBMS) but also by the severity which characterise these techniques (the length of the interruption of sexual promiscuity). The productions and the chemical composition of the milk of 23 farms (average 9000 buffaloes a year) were processed from 2011 to August 2016. The milk was daily conferred and analysed. We evaluated the milk production (kg), the percentage of fat, protein, lactose, dairy yield calculated with the equation of Altiero (1989), the values of the titratable acidity (°SH) and of pH. For each parameter, the monthly values of each farm were divided by the respective annual average and were expressed as an index (monthly values/annual average) in order to homogenize the graphical representations.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.037
GPT teacher head0.266
Teacher spread0.229 · 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 designBench or experimental
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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

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