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Record W2188170085 · doi:10.4141/cjas2011-032

S<scp>hort</scp>C<scp>ommunication</scp>: Analysis of intramuscular fat and fatty acids of different duck breeds and their association with SNPs of duck<i>A-FABP</i>gene

2011· article· en· W2188170085 on OpenAlexvenueno aff
Jun He, Lizhi Lu, Yong Tian, Zhengrong Tao, Deqian Wang, Jinjun Li, Guoqin Li, Junda Shen, Yan Fu, Dong Niu

Bibliographic record

VenueCanadian Journal of Animal Science · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsnot available
Fundersnot available
KeywordsIntramuscular fatSingle-nucleotide polymorphismFatty acidGeneBiologyGeneticsFood scienceBiochemistryGenotype

Abstract

fetched live from OpenAlex

He, J., Lu, L., Tian, Y., Tao, Z., Wang, D., Li, J., Li, G., Shen, J., Fu, Y. and Niu, D. 2011. Short Communication: Analysis of intramuscular fat and fatty acids of different duck breeds and their association with SNPs of duck A-FABP gene. Can. J. Anim. Sci. 91: 593–596. Intramuscular fat (IMF) is related to organoleptic characteristics of meat. Adipocyte fatty acid-binding protein (A-FABP) is one of the intracellular lipid-binding proteins involved in the transportation of fatty acids. The IMF contents of six duck breeds were measured, and the complete sequence and part of the 5' flanking region of duck A-FABP gene were obtained in this study. The IMF contents of different breeds were significantly different (P<0.05). Two SNPs were detected in the exon 3, one (HQ640428: g.2018A>G) was significantly associated with the contents of three fatty acids, total IMF and pectoral muscle weight. This work provides useful data for duck breeding.

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 score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.002

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 head0.011
GPT teacher head0.209
Teacher spread0.198 · 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

Citations9
Published2011
Admission routes1
Has abstractyes

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