Leprosy: a primer for Canadian physicians.
Bibliographic record
Abstract
Leprosy is a rare but serious infectious disease caused by Mycobacterium leprae. While global prevalence of the disease is decreasing, increasing rates of immigration from countries where leprosy is endemic have led to the recognition of this illness in North America. Classically, leprosy presents as hypopigmented cutaneous macules along with sensory and motor peripheral neuropathies, although the clinical manifestations vary along a disease spectrum. In addition to primary infection, patients may undergo a "reaction," an acute inflammatory response to the mycobacterium, which leads to pain and erythema of skin lesions and dangerous neuritis. Reactions can occur at any time during the course of leprosy, but they tend to be precipitated by treatment. They are a significant cause of impaired quality of life due to marked nerve damage and thus warrant prompt intervention. Although leprosy may have a protracted onset and be difficult to recognize, cure is achievable with appropriate multidrug therapy. Because untreated leprosy can result in permanent, irreversible nerve damage and secondary transmission, early diagnosis and treatment are essential to minimize morbidity.
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.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.052 | 0.016 |
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".