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Record W4361299615 · doi:10.1139/cjas-2022-0130

Amiata donkey body conformation, udder characteristics, and their relationship with milk yield and quality

2023· article· en· W4361299615 on OpenAlexvenueno aff
Federica Salari, Iolanda Altomonte, Carlo Boselli, Mina Martini

Bibliographic record

VenueCanadian Journal of Animal Science · 2023
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsnot available
Fundersnot available
KeywordsUdderDonkeyMilkingAnimal scienceVeterinary medicineBiologyMastitisMedicine

Abstract

fetched live from OpenAlex

To date, no selective actions have been taken to improve milk traits in dairy donkeys, and the characteristics of the udder are not well defined in relation to the productive characteristics. This study aimed at increasing knowledge on Amiata dairy donkey body conformation, udder traits, and their relationship with milk yield and quality. Morphological, udder, and teat measurements and milk evaluations of 45 pluriparous jennies were carried out. The average wither height of the jennies was 126 cm and the chest girth was 148 cm; a large standard deviation of some body measurements was found. Forty-nine percent of the animals showed a moderately developed udder, while most of the jennies had symmetrical half-udders (96%) and the intermammary cleft was clearly visible in 53% of subjects. Correlation analysis indicated that bigger animals tend to have bigger udders, higher teat diameter, and greater distance between teat tips. A positive correlation between the teat length and the milk fat was found ( p < 0.01), which suggests that jennies with longer teats have a better ability to release milk fat. The results of this paper may be useful to define the characteristics of the milking device and address selective choices of the animals.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.182
GPT teacher head0.376
Teacher spread0.194 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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