Epidemiology of<i>Malassezia</i>yeasts associated with pityriasis versicolor in Ontario, Canada
Bibliographic record
Abstract
The genus Malassezia was recently revised to include seven species, but the clinical significance of each of these species is not clearly understood. To obtain a better understanding of the contribution of individual Malassezia species to the epidemiology of pityriasis (tinea) versicolor, we used Leeming-Notman medium to culture patient skin specimens showing positive evidence of Malassezia infection in direct microscopy. Isolates were identified on the basis of recently published morphological and physiological tests for distinction of the new species. Identification using recently developed molecular criteria was also carried out for the ambiguous cases. Malassezia species were cultured from 111 cases of pityriasis versicolor in the Canadian province of Ontario. The most frequently isolated species were Malassezia sympodialis, M. globosa and M. furfur which respectively made up 59.4%, 25.2% and 10.8% of the isolated etiological agents. M. globosa was commonly isolated from a small number of pityriasis versicolor specimens obtained from investigators outside Canada. A large number of additional Ontario specimens with positive direct microscopy failed to yield a culture; however, it is suggested that this is consistent with the standard sampling practice of scraping the older portions of pityriasis lesions rather than the margins, where viable fungal cells are most likely to occur.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".