Implication of Ariaal sexual mixing on gonorrhea
Bibliographic record
Abstract
Recent research on sexual mixing in populations of sub-Saharan Africa raises the question as to whether STDs can persist in these populations without the presence of a core group. A mathematical model is constructed for the spread of gonorrhea among the Ariaal population of Northern Kenya. A formula for the basic reproduction number R(0) (the expected number of secondary infections caused by a single new infective introduced into a susceptible population) is determined for this population in the absence of a core group. Survey data taken in 2003 on sexual behavior from the Ariaal population are used in the model which is formulated for their age-set system including four subpopulations: single and married, female and male. Parameters derived from the data, and other information from sub-Saharan Africa are used to estimate R(0). Results indicate that, even with the elevating effect of the age-set system, the disease should die out since R(0) < 1. Thus, the persistence of gonorrhea in the population must be due to factors not included in the model, for example, a core group of commercial sex workers or concurrent partnerships.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".