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Imprinting, Sucking and Allosucking Behaviors in Buffalo Calves

2018· article· en· W2908664311 on OpenAlexvenueno aff
Patricia Mora‐Medina, Fabio Napolitano, Daniel Mota‐Rojas, J. Berdugo, Jhon Didier Ruíz Buitrago, Isabel Guerrero‐Legarreta

Bibliographic record

VenueJournal of Buffalo Science · 2018
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsImprinting (psychology)BiologyAnimal scienceGeneticsGene

Abstract

fetched live from OpenAlex

This paper provides a short review of the scientific literature, focusing on recent advances on the most representative events from birth to weaning, with special emphasis on the behavior and welfare of buffalo calves during the phases of imprinting, suckling and allosucking, based on the differences and similarities reported with dairy and beef cattle. The similarities include the facts that all 3 are gregarious animals whose dams separate from the herd prior to parturition to facilitate dam-calf bonding, and that maternal care fosters the ingestion of colostrum by the young. These species are also precocial and rely on mother – young mutual recognition for calf survival. In particular, mothers develop a selective bonding with their young soon after parturition, although buffalo cows seem to be tolerant to alien claves and are often engaged in communal nursing. In buffaloes and cattle negative emotions are induced by the stress brought on by early maternal separation. However, buffalo calves are more prone to express cross-sucking and contract neonatal diseases with higher mortality rates in intensive systems as compared to cattle. The review concludes that all three exhibit similar behaviors from parturition to weaning although the knowledge about the specific needs of buffalo calves should be increased and appropriate management practices implemented to improve their welfare state.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.369
Teacher spread0.320 · 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

Citations25
Published2018
Admission routes1
Has abstractyes

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