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Record W4403462319 · doi:10.1139/cjas-2024-0071

Total replacement of maize with raw or heat-treated sweet cassava tuber meal on productive performance and egg quality parameters in Jumbo quail hens from 6 to 14 weeks of age

2024· article· en· W4403462319 on OpenAlexvenueno aff
Ali Gazi, Caven Mguvane Mnisi

Bibliographic record

VenueCanadian Journal of Animal Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsQuailBiologyMealRaw materialFood scienceBiotechnologyEcology

Abstract

fetched live from OpenAlex

The impact of complete replacement of maize with raw or heat-treated sweet cassava ( Manihot esculenta) tuber meal (CTM) on productive performance and egg quality of Jumbo quail hens was determined. A total of 240, 6-week-old hens were randomly allocated to 60 cages (4 birds/cage) and assigned to five experimental diets with 12 replicates each. The diets were a standard layer mash diet without CTM (CON) and a standard layer mash diet in which 100% maize was replaced with raw (CTMR), boiled (CTMB), autoclaved (CTMA), and oven-dried CTM (CTMO). The highest overall feed intake, body weight gain, and final body weight ( P < 0.05) was observed from the CON group while the lowest was from the CTMB group. Overall FCR and mortality were not significantly influenced by the diets. Fourteen-week-old hens on CON had a higher ( P < 0.05) rate of lay than CTMR. Eggs from CON had the brightest yolk colour values than all the treatment groups. Moreover, eggs from CON had the least shape index than those from CTMO. Diet CTMA promoted heavier ( P < 0.05) eggshells than CTMR. Jumbo quail hens reared on maize-based diet showed better performance followed by autoclaving treatment, whereas boiling treatment compromised performance traits.

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 score0.003
Threshold uncertainty score0.006

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 head0.040
GPT teacher head0.266
Teacher spread0.226 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

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