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Record W4378390299 · doi:10.6000/1927-520x.2023.12.10

Growth Rate and Body Size Mapping of Male Buffaloes during the Fattening Phase

2023· article· en· W4378390299 on OpenAlex
I Putu Sampurna, Tjokorda Sari Nindhia, I Ketut Suatha

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Buffalo Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLivestock Farming and Management
Canadian institutionsnot available
Fundersnot available
KeywordsGrowth rateBiologyAnimal scienceBody weightMathematicsEndocrinology

Abstract

fetched live from OpenAlex

Background: Buffalo is an animal that really likes water. Generally, buffalo like to soak in muddy waters and swamps around the cage. This behavior appears because buffalo have very few sweat glands. Therefore, if one wants to develop buffalo farming, he/she should look for special habitats or existing buffalo breeding centers. Differences in growth rates are caused by physiological factors and functional demands. Growth in animal body size usually follows an exponential function, with the growth rate varying from one body size to another. An animal's body size that functions earlier will grow faster with a greater growth rate than an animal that functions later. Differences in the growth rate of animal body size are also influenced by the constituent components of these body parts. Body parts composed primarily of bone will develop earlier than those composed of muscle or fat. During fattening, the body size of male buffaloes will have a different growth rate, where this difference indicates the potential for body size. The body size of a buffalo with a high growth rate has relatively large growth potential, while those with a small growth rate have small growth potential, or the body part has stopped growing because it has reached its maximum point. The purpose of this study is to determine the body size growth rate of male buffaloes, which have high potential during fattening. Mapping the body size of male buffaloes during fattening aims to help breeders determine at what age the buffaloes start to be fattened and slaughtered for meat production purposes so that they are economically quite profitable.
 Methodology: Data was collected using a saturated sampling technique, in which the livestock taken were all buffaloes kept by the Sumber Sari Livestock Group in Kalianget village, Seririt District, Buleleng Regency, Bali, which met the requirements in terms of their health and physical condition. The data obtained were analyzed using the power model regression analysis to determine the growth rate of the body size of the buffaloes. To map the growth rate, Biplot analysis was carried out with a Promax rotation of 90, as the variable is the estimated body size of the buffaloes based on the equation of the power regression line, and the object is the age of the male buffaloes.
 Conclusion: The results showed that the fastest growth rate or the greatest potential was chest width, followed by hip width, chest depth, body length, chest circumference, and shoulder height. At the same time, the slowest part of the lowest potential was the height of the hips. The results of mapping the body size growth rate of male buffalo aged 11-74 months with biplot charts showed that their growth potential was still quite high. However, there was a tendency for male buffalo over 30 months to have a slower growth rate in body size than those under 30 months.

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.

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)0.002
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 score0.951
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.019
GPT teacher head0.239
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