Deepening Democracy in Indonesia? Direct Elections for Local Leaders (Pilkada). By Maribeth Erb and Priyambudi Sulistiyanto (eds.)
Bibliographic record
Abstract
Finding the genetic determinants of intermediate quantitative traits, such as serum creatinine and urea, might aid in finding the determinants of disease phenotypes, such as renal failure, that are, in part, defined according to threshold values imposed upon such traits. We evaluated the association between common variation in the gene encoding angiotensinogen, AGT, and the serum concentrations of creatinine and urea in non-diabetic Canadian Oji-Cree. We determined genotypes of the AGT codon 235 polymorphism among 502 non-diabetic Oji-Cree. We used multivariate analysis of variance to identify significant determinants of variation in serum concentrations of creatinine and urea and of systolic and diastolic blood pressure. We found significant associations between the AGT codon 235 genotype and serum concentrations of creatinine and urea (p = 0.017 and 0.049, respectively) and systolic blood pressure (p = 0.041). Compared with subjects with the other two genotypes, homozygotes for AGT T235/T235 had significantly lower serum concentrations of creatinine and urea and significantly higher mean systolic blood pressure. The findings suggest that the AGT T235 allele is a determinant of intermediate traits related to renal function in these aboriginal Canadians.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".