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Record W4388552935 · doi:10.1007/978-3-031-21020-4_10

Welfare at Calving and of the Growing Animals

2023· book-chapter· en· W4388552935 on OpenAlexaff
Margit Bak Jensen

Bibliographic record

VenueAnimal welfare · 2023
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsAnimal welfareWelfareWeaningIce calvingAnimal scienceAnimal-assisted therapyDairy cattleVeterinary medicineBiologyPet therapyPolitical scienceLactationMedicinePregnancyLaw

Abstract

fetched live from OpenAlex

Dairy cows and their calves face several challenges around parturition and in the early life of the calf that impact their welfare. There is an increasing public awareness of some of these challenges, including those that begin before birth as the cow prepares for labour and continue until the calf is weaned from milk. Researchers have recognised that these challenges exist and have begun to define the key animal welfare issues for the cow and calf during this time period. In this chapter, we review the experience of the cow around the time of calving, the effect of prolonged maternal contact on the dam and her calf, and social housing for young calves. Next, we discuss the welfare of youngstock post-weaning and of growing cattle, although this topic has received less research attention. We end the chapter with a discussion about advances and future challenges in animal welfare for the peri-parturient cow and her calf, as well as the growing animal.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.005

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 head0.027
GPT teacher head0.220
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), 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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