MétaCan
Menu
Back to cohort
Record W2041966849 · doi:10.1038/srep07166

Effects of Rhodiola on production, health and gut development of broilers reared at high altitude in Tibet

2014· article· en· W2041966849 on OpenAlexaff
Long Li, Honghui Wang, Xin Zhao

Bibliographic record

VenueScientific Reports · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMedicinal Plants and Bioactive Compounds
Canadian institutionsMcGill University
Fundersnot available
KeywordsAltitude (triangle)BiologyRhodiolaMathematics

Abstract

fetched live from OpenAlex

Rhodiola has long been used as a traditional medicine to increase resistance to physical stress in humans in Tibet. The current study was designed to investigate whether Rhodiola crenulata (R. crenulata) could alleviate the negative effects of hypoxia on broiler chickens reared in Tibet Plateau. The effect of supplementing crushed roots of R. crenulata on production performance, health and intestinal morphology in commercial male broilers was investigated. Dietary treatments included CTL (basal diet), Low-R (basal diet + 0.5% R. crenulata) and High-R (basal diet + 1.5% R. crenulata). In comparison with broilers fed the control diet, Low-R had no effect on production performance while High-R significantly decreased average daily feed intake at d 14, 28 and 42, body weight at d 28 and 42 and gut development. Ascites induced mortality did not differ among treatments. Nevertheless Low-R significantly reduced non-ascites induced mortality and total mortality compared with broilers fed CTL and High-R diets. Broilers fed the High-R diet had significantly increased blood red blood cell counts and hemoglobin levels at 28 d compared with other treatments. Our results suggest that supplementation with Rhodiola might reduce the effects of hypoxia on broilers and consequently decrease mortality rate.

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 integrity0.0000.001
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 head0.007
GPT teacher head0.239
Teacher spread0.232 · 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

Citations24
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueScientific ReportsSame topicMedicinal Plants and Bioactive CompoundsFrench-language works237,207