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Linear Body Measurements and Carcass Characteristics of Rabbits Fed Orange (Citrus sinensis) Waste Meal as Alternative Fibre Source in Diet

2013· article· en· W1870476259 on OpenAlexvenueno aff
Alexander Henry, G. A. William, O. O. Effiong

Bibliographic record

VenueAdvances in natural science/Advances in natural sciences · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRabbits: Nutrition, Reproduction, Health
Canadian institutionsnot available
Fundersnot available
KeywordsOrange (colour)MealAnimal scienceBiologyBreedVeterinary medicineCompletely randomized designLinear relationshipBody weightCrossbreedFood scienceMedicineMathematicsEndocrinology

Abstract

fetched live from OpenAlex

A study was conducted to assess the effect of orange waste meal as an alternative fibre source on linear body measurements of rabbits. Twenty-four (24) weaned rabbits of cross breed and mixed sexes were used for the study. Experimental animals which weighed between 676.67g to 686.67g were allotted to four dietary treatments in a completely randomized design. Results of the study showed that head length (HL), body length (BL), heart girth (HG), length of hind limb (LHL) and length of fore limb (LFL) differed (p 0.05) statistically between the treatment groups. At the end of the experimental period of ten weeks, rabbits fed diet T 4 (endocarp + mesocarp) recorded higher (p 0.05) influenced by dietary treatments. Therefore, rabbits can effectively utilize orange waste meal as an alternative fibre source without adverse effects on linear body measurements 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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.287
Teacher spread0.269 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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