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Record W2265922366

Estimation of heritability and genetic correlations of body weight in different age for three strains of Japanese quail

2007· article· en· W2265922366 on OpenAlexaboutno aff
M Shokoohmand, Nasser Emam Jomeh Kashan

Bibliographic record

VenueInternational Journal of Agriculture and Biology (Pakistan) · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsQuailHeritabilityRestricted maximum likelihoodSireBiologyBody weightSelection (genetic algorithm)Animal scienceGenetic correlationGeneticsGenetic variationMaximum likelihoodStatisticsEcologyGeneEndocrinologyMathematics
DOInot available

Abstract

fetched live from OpenAlex

In this study genetic parameters of body weight were estimated for three commercial strains of Japanese quail (White, Canadian wild & Brown). Live body weight at 14, 28 and 42 days of age on approximately 900 quail of both sexes from 55 each of sires and dams in each strain were utilized to estimate genetic parameters. The chicks hatched of each sire and dam identified by the same color, and at 10 days of age they were wing-tagged with an aluminum plate. The first weighing was done at 14 days and repeated at 28 and 42 days of age. Analysis was carried out with the records on 900 quails in three strains. Data were analyzed using restricted maximum likelihood (REML) with relationship matrix. The moderate to high heritability for most study traits suggested that selection to increase or decrease these traits will be successful. The genetic correlations of body weight (BW) at different ages, measurements were positive and tended to be moderate to high. These results showed that selection for weight at early ages will have a positive effect on weight at later ages.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.020
GPT teacher head0.293
Teacher spread0.273 · 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 designObservational
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

Citations29
Published2007
Admission routes1
Has abstractyes

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