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Record W4404173871 · doi:10.1139/cjas-2024-0084

The effect of temperature and humidity index on egg-laying and hatching parameters in Japanese quail

2024· article· en· W4404173871 on OpenAlexvenueno aff
Hüseyin Baki Çiftçi

Bibliographic record

VenueCanadian Journal of Animal Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsCageAnimal scienceHatchingQuailHeat indexFeed conversion ratioYolkRelative humidityBiologyBody weightEcologyMathematicsHeat stressEndocrinology

Abstract

fetched live from OpenAlex

The objective was to measure the effect of temperature–humidity index (THI) on egg-laying and hatching parameters. Quails were randomly transferred to two cage blocks at 20.55 ± 0.05 °C and 52.25 ± 0.68% relative humidity (RH), accepted as 66 THI group. One cage block was transferred to the next room at 16.15 ± 0.13 °C and 70.77 ± 0.38% RH considered as 61 THI group. In the second stage of the study, the cage block previously accepted as 61 THI group was considered as to 69 THI group by rising up the temperature to 21.97 ± 0.18 °C. The group previously considered as 66 THI group was accepted as 76 THI group by rising up the temperature to 28.06 ± 0.02 °C. Feed consumption and egg weight were significantly decreased, in 69 and 76 THI groups. Daily egg production was lower in 61 and 66 THI groups than that in 69 THI group. In 76 THI group, shell weight and yolk height were decreased. High THI caused negative effects on feed consumption, egg weight, egg quality, and feed conversion ratio.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

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 head0.013
GPT teacher head0.237
Teacher spread0.223 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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