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Performance and behavior of dairy calves fed diets containing milk and citric flavor agents

2007· article· en· W2008290662 on OpenAlexfundno aff
Silvane Barcelos Carlotto, Clair Jorge Olivo, Júlio Viégas, D. A. Stiles, Alexandre Mossate Gabbi, Karen Döering Brustolin, Pablo Santini Charão, Grasiela Rossarolla, Magnos Fernando Ziech, Lilian Elgalise Techio Pereira, Luciene Fernanda de Barros Scaravelli

Bibliographic record

VenueCiência e Agrotecnologia · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsnot available
FundersCanada Millennium Scholarship Foundation
KeywordsDry matterWithersAnimal scienceFlavorAromaHayRuminatingChemistryFood scienceBiologyBody weightRumination

Abstract

fetched live from OpenAlex

While young ruminants prefer milk aroma and researches about this theme are being developed, the use of citric aroma, very appetized for older ruminants, are low utilized to young animals. This work aims to compare the influence of milk and citric flavor agents on the diets of nursing dairy calves. In this trial, 12 animals of Holstein breed were distributed in a randomized block design with four treatments (concentrate without flavor agent, concentrate with milk flavor or citrus flavor, and concentrate with milk plus citrus flavor agent) and three repetitions. The parameters evaluated were: concentrate dry matter intake (CDMI), hay dry matter (HDMI), milk dry matter intake (MDMI) and total dry matter intake (TDMI), average weight gain (ADWG), feed conversion (FC), initial (IBW) and final body weight (FBW), initial thoracic perimeter (ITP) and final thoracic perimeter (FTP), initial abdominal perimeter (IAP) and final abdominal perimeter (FAP), initial withers height (IWH) and final withers height (FWH) and animal behavior. The CDMI, HDMI and TDMI, as well as IBW, FBW, ITP, FTP, IAP, FAP, IWH and FWH did not show differences (P>0.05). The averages daily gain and feed conversion showed no differences, with means of 0.55 kg/animal and 2.09, respectively. The diets did not affect animal behavior parameters (P>0.05).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.044
GPT teacher head0.259
Teacher spread0.215 · 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

Citations9
Published2007
Admission routes1
Has abstractyes

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