Risk factors for the incidence of calcium oxalate uroliths or magnesium ammonium phosphate uroliths for dogs in Ontario, Canada, from 1998 to 2006
Bibliographic record
Abstract
OBJECTIVE: To investigate individual- and community-level contextual variables as risk factors for submission of calcium oxalate (CaOx) uroliths or magnesium ammonium phosphate (ie, struvite) uroliths for dogs to a national urolith center, as determined on the basis of urolith submission patterns. SAMPLE POPULATION: Records of 7,297 dogs from Ontario, Canada, with CaOx or struvite uroliths submitted to the Canadian Veterinary Urolith Centre from 1998 through 2006. PROCEDURES: Data were analyzed via multilevel multivariable logistic regression. RESULTS: Individual-level main effects and interactions significantly associated with the risk of submission of CaOx uroliths rather than struvite uroliths included age, sex, breed group, neuter status, body condition, dietary moisture content, diet type, sex-neuter status interaction, sex-age interaction, body condition-age interaction, and breed group-dietary moisture content interaction. In addition, median community family income and being located within a major urban center (ie, Toronto) were significant risk factors for submission of CaOx uroliths, compared with submission of struvite uroliths. CONCLUSIONS AND CLINICAL RELEVANCE: Individual-level and dietary factors for dogs affected the risk of submission of CaOx uroliths, relative to that of struvite uroliths. Interactions among these variables need to be considered when assessing the impact of these risk factors. In addition, community-level or contextual factors (such as community family income and residing in a densely populated area of Ontario) also affected submission patterns, although most of the variance in the risk for submission of CaOx uroliths, compared with the risk for submission of struvite uroliths, was explained by individual-level factors.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".