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Record W2935876544 · doi:10.5539/jas.v11n5p547

Physical and Chemical Quality Profile of Lamb Meat Which Was Swamp Buffalo’s Rumen Liquid Based Fodder-Fed

2019· article· en· W2935876544 on OpenAlexvenueno aff
Tintin Rostini, Danang Biyatmoko, Irwan Zakir, Arief Hidayatullah

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood and Agricultural Sciences
Canadian institutionsnot available
FundersDirektorat Jenderal Pendidikan Tinggi
KeywordsFodderRumenAnimal scienceBiologySwampSignificant differenceVeterinary medicineChemistryFood scienceAgronomyMathematicsMedicineEcology

Abstract

fetched live from OpenAlex

This study aims to know the effect of swamp buffalo’s rumen liquid based fodder toward physical and chemical quality of lamb meat. This study used 12 male Kacang goats at age of 10-12 months with weight around 12±1.2 kg. Method used in this study was Completely Randomized Design with 4 treatments repeated for 3 times until it reached 12 units of trials. The treatments consist of: (PS), regular fodder given by breeder (PFCK1) 25% rumen liquid based fodder + 75% PS. (PFCK2), 50% rumen liquid based fodder + 50% PS. (PFCK3) 75% rumen liquid based fodder + 25% PS. Data was statistically analyzed by using variance analysis. Difference between treatments was tested by using Duncan’s New Multiple Range Test. Study results showed that the usage of rumen liquid based fodder of 75% increased protein and lamb fat content (P < 0.05), the lamb meat was physically more tender (P < 0.05). The conclusion is swamp buffalo’s rumen liquid could be used to enhance lamb meat quality.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.296

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.017
GPT teacher head0.244
Teacher spread0.228 · 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 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

Citations1
Published2019
Admission routes1
Has abstractyes

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