Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: The number of fungal infections occurring each year in Iran is not known. As the burden of fungal disease is a measure used to assess and compare the relative impact of different type of fungal diseases on populations, we have estimated the burden of fungal diseases in Iran. METHODOLOGY: We estimated the burden of human fungal diseases based on the specific populations at risk, existing epidemiological data in both local and international databases, and modelling previously described by the LIFE program (http://www.LIFE-worldwide.org). RESULTS: Among the population of Iran (79,926,270 in 2016), 6,670,813 (8.3%) individuals are estimated to suffer from a fungal infection each year. A total of 2,791,568 women aged between 15 and 50 years are estimated to suffer from recurrent vulvovaginal candidiasis, annually. In addition, considering the 13.3% prevalence rate of tinea capitis in children, a total of 2,552,624 cases per year are estimated. The estimated burden of invasive aspergillosis in the 3 groups of patients with hematologic malignancy, lung cancer and chronic pulmonary obstructive disease was 6394 (8.0 per 100,000). The estimate for the burden of allergic disease related to fungi including allergic bronchopulmonary aspergillosis, severe asthma with fungal sensitization and allergic fungal rhinosinusitis was 272,095 (340 per 100,000). Based on the 28,663 cases of HIV infection reported, an estimated 900 and 113 cases with pneumocystosis and cryptococcal meningitis are annually anticipated, respectively. CONCLUSION: Our estimates indicate that the importance of fungal infections is high but overlooked in Iran, which warrants further actions by health care authorities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it