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Record W2152442330 · doi:10.3382/ps.2011-01799

Effect of genetic selection on growth parameters and tonic immobility in Leghorn pullets

2012· article· en· W2152442330 on OpenAlexaboutno aff
Kenneth E. Anderson, D.R. Jones

Bibliographic record

VenuePoultry Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyAnimal scienceSelective breedingCorticosteroneTonic (physiology)Stock (firearms)BroodZoologyEndocrinologyEcology

Abstract

fetched live from OpenAlex

Four genetic stocks of Leghorn pullets were used to evaluate the effects of genetic selection on growth and fearfulness behavior. Three of the stocks were the Ottawa randombred control stocks from 1950 (CS5), 1959 (CS7), and 1972 (CS10). The fourth stock was a 1993 commercial laying stock (CCS) whose ancestors were involved in the formation of the randombred control stocks. Pullets were reared in a brood and grow poultry house with flat deck cages. Each stock was comprised of 840 birds with 21 replicates per strain. Body weight and feed consumption were monitored biweekly. At 16 wk of age, a 20-hen sample from each strain was analyzed for BW, body composition, and tonic immobility. There were significant (P < 0.05) differences among the stocks for BW of 1,403; 1,333; 1,332; and 1,428 g for the CS5, CS7, CS10, and CCS stocks, respectively. Furthermore, significant differences occurred with regard to feed consumption, livability, and frame size. There were no differences among the stocks in tonic immobility. Measurement of circulating corticosterone levels were shown to be significantly (P < 0.05) higher in the CCS stock (7.64 ng/mL) than for both the CS5 (4.50 ng/mL) and CS7 (4.61 ng/mL) stocks, whereas the CS10 stock was intermediate with 6.45 ng/mL. Genetic selection has affected growth parameters, although there appears to be no change in fearfulness behavior but an increase in corticosterone levels in stocks from later years.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.098

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.239
Teacher spread0.229 · 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 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

Citations12
Published2012
Admission routes1
Has abstractyes

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