Polymorphisms of the <i>prion protein</i> gene (<i>PRNP </i>) in Alaskan moose (<i>Alces alces gigas</i>)
Bibliographic record
Abstract
sion assays on the Sequenom MassArray TM system (San Diego, CA, USA).Analysis of the USMARC swine mapping family resulted in a map assignment of INHA to chromosome 15 at position 88 cM and generated 67 informative meioses in seven families (86 progeny).The STAR marker generated 43 informative meioses and mapped to chromosome 15 at position 61 cM, the same position as microsatellite marker SW1401 on the MARC swine linkage map (http://www.marc.usda.gov/).The T allele at nucleotide 499 was found only in Meishan with a frequency of 0.8.Association of SNPs with ovulation rate or age of puberty: Onequarter of Meishan F 8 gilts (n ¼ 150) that were descendants of the MARC resource population 1 with age at puberty and ovulation rate data were genotyped for the INHA 572G>A and STAR 499G>T polymorphisms.Data were analysed using the GLM procedure of SAS in which sire and maternal grandsire were fitted as fixed effects for age at puberty.The model for ovulation rate also included a fixed effect for method of measuring ovulation rate (laparoscopy versus slaughtered).The frequencies of the rare alleles were 0.32 (X03265:c.572G>A of INHA) and 0.19 (U53020:c.499G>T of STAR) respectively.The INHA and STAR genotypes were not associated with ovulation rate (P ¼ 0.84 and P ¼ 0.95 respectively) or age at puberty (P ¼ 0.32 and P ¼ 0.75 respectively) in this data set.Due to a lack of association of these single nucleotide polymorphism (SNPs) with ovulation rate, we suggest that the linkage disequilibrium between the causative mutation and these genes has been disrupted by recombination in this population, and the gene responsible for the QTL effects on porcine chromosome 15 probably resides some distance away from INHA and STAR.
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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 | 0.001 | 0.001 |
| 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".