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Record W4378471602 · doi:10.1016/j.anopes.2023.100043

Lactational performance of cows fed extruded flaxseed in commercial dairy herds

2023· article· en· W4378471602 on OpenAlexaffabout
A. Beauregard, Marie-Pierre Dallaire, R. Gervais, P.Y. Chouinard

Bibliographic record

VenueAnimal - Open Space · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsLactoseAnimal scienceHerdMilk fatLactationBiologyFood scienceLinseed oilPregnancy

Abstract

fetched live from OpenAlex

The objective of the current on-farm trial was to assess the impact of feeding extruded flaxseed on milk yield and composition. Thirty commercial dairy herds located in the province of Québec, Canada were recruited. The experiment began with a baseline period of 2 months during which each cow received their regular diets. Data collected during this period were used as covariate. Farms were then randomly allocated into a control group (n = 15; 767 cows) which continued to receive their regular diets, or a treatment group (n = 15; 863 cows) which received diets supplemented with extruded flaxseed (0.7 kg/d per cow) during an experimental period of 7 months. Significance was declared at P ≤ 0.05 and tendencies at 0.05 < P ≤ 0.10. Feeding extruded flaxseed did not affect feed intake but increased milk yield by 1.1 kg/d per cow, and feed efficiency by 6.5%. Dietary addition of extruded flaxseed increased milk fat (tendency) and lactose yield, whereas milk protein yield was similar between treatments. Estimated CH4 intensity were reduced by 1.3 g/L of milk (−9.2%) in herds receiving extruded flaxseed. Feeding extruded flaxseed increased milk fat concentration of cis-9, cis-12, cis-15 18:3 and total n-3 fatty acids. Results of the current on-farm trial confirm observations made under experimental conditions that feeding moderate levels of extruded flaxseed improves production performance in dairy cows.

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)0.000
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 score0.779
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.052
GPT teacher head0.292
Teacher spread0.241 · 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

Citations6
Published2023
Admission routes2
Has abstractyes

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