Northern tropics? Seven cases of pyomyositis in northwestern Ontario
Bibliographic record
Abstract
OBJECTIVE: To document the incidence and clinical characteristics of (tropical) pyomyositis in a predominantly First Nations population in northwestern Ontario. METHODS: The present study was a retrospective case series conducted over a 38-month period in a population of 29,105 in northwestern Ontario. RESULTS: The authors identified seven cases of pyomyositis and describe demographics, comorbidity, clinical course, and the results of imaging and microbiology investigations. The incidence of pyomyositis in northwestern Ontario is 7.6 cases per 100,000 person-years, a rate that is approximately 15 times higher than the only published incidence rate for a developed country (Australia). CONCLUSION: The rate of pyomyositis is high. It may be mediated by overcrowded housing, inadequate access to clean water, and high background rates of methicillin-resistant Staphylococcus aureus infection, injection drug use, and type 2 diabetes mellitus.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".