MétaCan
Menu
Back to cohort
Record W2521851194 · doi:10.1139/cjas-2015-0203

Performance and carcass characteristics of cattle fed lipid sources in the diet

2016· article· en· W2521851194 on OpenAlexvenueno aff
Érico da Silva Lima, Jozivaldo Prudêncio Gomes de Morais, Roberto de Oliveira Roça, Tiago Neves Pereira Valente, Ernani Nery de Andrade, Bruno Borges Deminicis

Bibliographic record

VenueCanadian Journal of Animal Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsnot available
FundersInstituto Federal GoiásUniversidade Estadual Paulista
KeywordsDry matterCottonseedUreaNeutral Detergent FiberCottonseed mealAnimal scienceChemistryForageMealWeight gainPulp (tooth)Food scienceFeed conversion ratioSoybean mealBody weightBiologyAgronomyBiochemistryMedicine

Abstract

fetched live from OpenAlex

The aim of this study was to determine the effect of the inclusion of different lipid sources [whole cottonseed (CS) and protected fat in diets containing sugarcane, corn, citrus pulp, CS meal, and urea] on animal performance, hot carcass dressing (HCD), ribeye area (RA), fat thickness (FT), and postmortem pH of the meat of Nellore cattle during finishing. The treatments evaluated were feed with 2.50% CS (control diet, T1 treatment); feed with 11.50% CS (high CS, T2 treatment); and feed with 3.13% CS added of protected lipid (PL) (T3 treatment), all on a DM basis. The forage:concentrate ratio of the diet was 50:50. Thirty-nine intact steers with average initial body weight of 494 kg and 36 months old were confined for 63 d. The addition of lipid sources tested in this study did not affect dry matter intake, crude protein intake, neutral detergent fiber intake, final live weight, average daily weight gain, HCD, RA, FT, and meat pH. It was concluded that the addition of PLs in the diet did not affect weight gain and carcass characteristics.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.215
Teacher spread0.194 · 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 designBench or experimental
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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Animal ScienceSame topicRuminant Nutrition and Digestive PhysiologyFrench-language works237,207