Novel BsuRI-c.930A>G-FSHb Associated with Litter Size Traits on Large White X Landrace Crossbred Sows
Bibliographic record
Abstract
The objective of this experiment was to identify the novel single nucleotide polymorphisms (SNPs) on porcine follicle stimulating hormone b subunit (FSHb) genes. Moreover, their association with litter size traits in commercial pigs will be analyzed. 1,155 Large White x Landrace crossbred sows were bled and DNA was extracted. The records included total number of piglet born (TNB), number of piglet born alive (NBA), number of piglets stillbirth (SB) and number of piglets mummified (MM). The known sequence of porcine FSHb (GenBank accession no. D00621.1) was screened homology to known sequences in term of express sequenced tags (ESTs) in public domain, GenBank. The primers were designed for amplified the novel BsuRI-c.930A>G-FSHb fragment which confirmed by PCR-RFLP and nucleotide sequencing then genotyping. The favorable cut homozygous G/G allele was highly significant higher than A/G allele in terms of TNB and NBA. While, published marker HaeIII-g.5894A>G-FSHb was not significant difference in any litter traits. For haplotype analysis, c.930A>G-g.5894A>G of FSH?, unfavorable GG/AA haplotype was significantly lower TNB and NBA than other haplotypes. Conversely, this haplotype was significantly higher MM than others. The study concluded that BsuRI-c.930A>G and the haplotype of HaeIII-g.5894A>G - BsuRI-c.930A>G of FSHb may used for marker-assisted selection on pig breeding program.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".