Sexually Transmitted Disease Core Theory: Roles of Person, Place, and Time
Bibliographic record
Abstract
The authors’ purpose was to expand sexually transmitted disease core theory by examining the roles of person, place, and time in differentiating geographic core areas from outbreak areas. The authors mapped yearly census-tract-level syphilis rates for San Francisco, California, based on new primary and secondary syphilis cases reported to the San Francisco City sexually transmitted disease surveillance program between January 1, 1985, and December 31, 2007. SaTScan software (Information Management Services, Inc., Silver Spring, Maryland) was used to identify geographic clusters of significantly elevated syphilis rates over space and time. The authors graphed epidemic curves for 1) core areas, 2) outbreak areas, 3) neither core nor outbreak areas, and 4) noncore areas, where noncore areas included outbreaks, and stratified these curves according to demographic characteristics. Five clusters of significantly elevated primary and secondary syphilis rates were identified. A 5-year threshold was useful for differentiating core clusters from outbreak clusters. Epidemic curves for core areas, outbreak areas, neither core nor outbreak areas, and noncore areas were perfectly synchronized in phase trends and wavelength over time, even when broken down by demographic characteristics. Between epidemics, the occurrence of syphilis affected all demographic groups equally. During an epidemic, a temporary disparity in syphilis occurrence arose and a homogeneous core group of cases could be defined.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".