Reply to Dr. Charlebois et al. ( Clin Infect Dis 2002; 34:425–33 )
Bibliographic record
Abstract
Sir—In their study of the community prevalence of carriage of methicillin-resistant Staphylococcus aureus (MRSA) among San Francisco's urban poor, Charlebois et al. [1] found an overall prevalence of MRSA carriage of 2.8%. Injection drug use and prior hospitalization within 1 year were significant multivariate risk factors for MRSA acquisition. During the spring of 2000, a similar point prevalence study of MRSA nasal carriage among injection drug users (IDUs) in the downtown east side of Vancouver, British Columbia, was conducted jointly by the Communicable Disease Control Division of the Vancouver/Richmond Health Board and the Division of Medical Microbiology and Infection Control, Vancouver Hospital and Health Sciences Centre (VHHSC). Vancouver has a large concentration of economically disadvantaged individuals in the downtown east side of the city core. This inner-city neighborhood is home to 47,940 people, 52% of whom live below the poverty level. The life expectancy for men is 65.8 years, compared with 79.9 years in Vancouver's wealthiest neighborhood [2]. The area provides services for 12,000 IDUs, many of whom live in the area's ∼500 single-room–occupancy hotels [3]. Approximately 3,000,000 needles are dispensed annually through the needle-exchange program [4].
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.045 | 0.026 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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".