EXCLUSION MAPPING OF MAJOR CRYSTALLIZATION INHIBITORS IN IDIOPATHIC CALCIUM UROLITHIASIS
Bibliographic record
Abstract
PURPOSE: We determined whether genetic variation at 3 loci coding for putative crystallization inhibitors is linked to calcium urolithiasis. MATERIALS AND METHODS: We studied a cohort of 64 French-Canadian sibships including multiple recurrent calcium stone formers, comprising 154 independent pairs of siblings with at least 1 stone episode. Physical and meiotic mapping of the genes coding for osteopontin and uromodulin (Tamm-Horsfall protein) as well as the osteocalcin related gene (ORG or putative nephrocalcin) was performed and microsatellite markers were identified. We used nonparametric linkage analysis in the whole affected sib pair cohort as well as in affected pairs without hypercalciuria, that is concordant for 24-hour urine calcium excretion in the first quartile (mean plus or minus standard deviation 0.053 +/- 0.020 mmol./kg. or 3.4 +/- 1.3 mmol. daily), and in the first and second quartiles (mean 0.064 +/- 0.027 mmol./kg. or 4.9 +/- 2.1 mmol. daily, respectively). RESULTS: Lod scores were less than 0.3 for all 3 loci using these affection statuses. Further analysis enabled the exclusion of uromodulin at (relative risk or lambda = 3.9 and 2.5), osteopontin (lambda = 2.7 and 1.6) and ORG (lambda = 5.5 and 3.7) for affected sib pairs concordant for urine calcium excretion in the lowest and 2 lowest quartiles, respectively. CONCLUSIONS: Loci encoding 3 crystallization inhibitors are unlikely to be major genes involved in calcium stone formation in our population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".