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Record W4210821951

Male dairy calf welfare: A Canadian perspective on challenges and potential solutions.

2022· article· en· W4210821951 on OpenAlexaffabout
Lexie M Reed, D.L. Renaud, T.J. DeVries

Bibliographic record

VenuePubMed · 2022
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAnimal welfareWelfareDairy industryAnimal husbandryWelfare economicsPolitical scienceMedicineAgricultureBiologyEconomicsEcologyFood science
DOInot available

Abstract

fetched live from OpenAlex

Male dairy calf welfare is a key issue in the Canadian cattle industry. The welfare of male dairy calves can be explored through the aspects of health and biological functioning, affective states, and natural living. Presently, the main welfare issues associated with the production of male dairy calves include morbidity and mortality, colostrum and feeding management, transportation, isolation, castration and disbudding, and euthanasia. Opportunities to improve male dairy calf welfare include improving accepted industry practices, enhancing education and compliance with industry codes of practice, and increasing veterinarian involvement in on-farm animal welfare. The benefits of improving male dairy calf welfare include maintenance of the cattle industry's social license and improved producer mental health and occupational satisfaction. The main barriers to improving male dairy calf welfare are economics and cultural attitudes within the industry towards male dairy calves.

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)0.007
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.370

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0090.005
Scholarly communication0.0060.003
Open science0.0030.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.072
GPT teacher head0.273
Teacher spread0.201 · 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 designNot applicable
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

Citations9
Published2022
Admission routes2
Has abstractyes

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