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Record W2988799330 · doi:10.3390/ani9110938

Dietary Inositol Reduces Fearfulness and Avoidance in Laying Hens

2019· article· en· W2988799330 on OpenAlexaff
Eugenia Herwig, H.L. Classen, C.L. Walk, M.R. Bedford, K. Schwean-Lardner

Bibliographic record

VenueAnimals · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsInositolBiologyAnimal scienceInternal medicineEndocrinologyMedicineBiochemistry

Abstract

fetched live from OpenAlex

Myo-inositol (inositol) affects memory, and the incidence of depression and anxiety in mammals. An experiment was designed to determine if pure inositol (0.16%), or high levels of phytase (3000 FTU/kg) affect the behaviour of fully beaked Lohmann LSL lite hens fed amino acid sufficient (19% crude protein (CP)) and deficient diets (16% CP), from 19 to 59 weeks of age. The data collected included live-scan behaviour observations and novel object (NO) tests (both at 1, 10 and 40 weeks of the trial); heterophil-to-lymphocyte (H/L) ratios (week 1 and week 40 of the trial); end of trial feather cover, and comb and skin lesions; and daily mortality. Reducing CP increased sitting by 2.5%. Inositol, but not phytase, reduced the latency to peck at the NO by 300 sec. Inositol reduced vent feather cover by 12% and tended to increase mortality by 13%. No effects on H/L ratio, and comb or skin lesions were found. In conclusion, regardless of the source, inositol reduced vent feather cover, while it tended to increase mortality. Only pure inositol reduced fearfulness in laying hens.

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 score0.002
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 head0.014
GPT teacher head0.211
Teacher spread0.197 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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