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Record W2091536114 · doi:10.3168/jds.2007-0085

Use of Flavored Drinking Water in Calves and Lactating Dairy Cattle

2007· article· en· W2091536114 on OpenAlexaff
Linda Thomas, Tom Wright, A. Formusiak, J.P. Cant, V.R. Osborne

Bibliographic record

VenueJournal of Dairy Science · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEffects of Environmental Stressors on Livestock
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsStarterWater intakeOrange (colour)Dry matterFlavorDairy cattleAnimal scienceLatin squareLactationWater consumptionFeed conversion ratioWeight gainChemistryFood scienceAgronomyBiologyBody weightEnvironmental scienceRumenEnvironmental engineering

Abstract

fetched live from OpenAlex

Experiments were conducted to investigate the use of added flavor in drinking water of Holstein calves and lactating dairy cattle to determine effects on dry feed intake. Nine calves were used in a replicated 3 x 3 Latin square design, and water offered was unflavored or flavored with orange or vanilla. All calves were offered commercial starter. Feed intake of the dry starter was increased in calves offered the orange flavor treatment compared with the control or the vanilla treatment. The increased dry feed intake agreed with the significant increase in weight gain measured in calves on the orange treatment. Further experiments were performed with 4 second-lactation cows using the addition of another orange flavor to the water compared with unflavored water under conditions of free access or time-restricted water access. No significant changes were found for dry matter intake, water consumption, or milk yield. These findings demonstrate an important finding that flavoring agents need not be added only to the starter feed for calves, but flavor can stimulate dry feed intake and BW gain when used in drinking water.

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 score0.668
Threshold uncertainty score0.139

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 communication0.0000.001
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 head0.021
GPT teacher head0.242
Teacher spread0.221 · 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

Citations36
Published2007
Admission routes1
Has abstractyes

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