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Record W4405379929 · doi:10.1079/9781800625136.0007

Robotic Milking of Dairy Cows: Behaviour and Welfare

2024· book-chapter· en· W4405379929 on OpenAlexaff
M.T.M. King, Ashlyn Scott, Gabriel Machado Dallago, Ed Pajor, T.J. DeVries

Bibliographic record

VenueCABI eBooks · 2024
Typebook-chapter
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of ManitobaUniversity of GuelphUniversity of Calgary
Fundersnot available
KeywordsMilkingWelfareAnimal scienceAutomatic milkingAnimal welfareDairy cattleAgricultural scienceBusinessEconomicsEnvironmental scienceBiologyMarket economyEcologyLactationIce calving

Abstract

fetched live from OpenAlex

This chapter describes cow behaviour, health and welfare in dairy herds using robotic (automated) milking systems (AMS). First, we discuss three key aspects of milking that differ in AMS herds compared to conventional systems: milking is automated, cows are milked and offered supplemental feed on an individual basis, and milking times are unscheduled and variable. Next, we discuss how cows must be managed differently in AMS herds, not only in terms of training, motivating and directing cows to visit the AMS, but also in relation to monitoring cow health and detecting illness using precision technologies that may be associated with AMS.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.833
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.299
Teacher spread0.244 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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