Epidemiology of urolithiasis in dogs from Guadalajara City, Mexico
Bibliographic record
Abstract
Urolithiasis is a frequent and recurrent problem in dogs around the world. Several epidemiological studies based on mineral composition of uroliths have been carried out in different geographical areas. The objective of this study was to analyze epidemiological data of 195 dogs with urolithiasis from the metropolitan area of Guadalajara Jalisco, Mexico. To determine the chemical composition of uroliths, quantitative and qualitative analyses were performed by means of stereoscopic microscopy and infrared spectroscopy. The dogs` median age was six years and a male-female ratio of 1.4:1 was observed. The most affected pure breed dogs were schnauzer, poodle, Labrador retriever, Yorkshire terrier, and German shepherd. The frequency of uroliths of struvite, calcium oxalate, urates, mixes, and compounds, is similar to the one found in other studies performed in other populations. However, a much higher frequency of silicate-containing uroliths (16.92%) was observed, both in a pure form as well as in mineral mixtures. These results led us to suggest the need to develop further investigations to determine the origin of this high frequency.Figure 1. Different types of uroliths. Note the differences in shape, size, color, and number; however, none of these characteristics is specific to a particular mineral composition.
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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 | 0.002 | 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) | 0.001 | 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".