Relapsing fever <em>Borrelia</em> in California: a pilot serological study
Bibliographic record
Abstract
BACKGROUND: (RFB) in human disease. In this pilot study, we have evaluated serological reactivity against Bb and RFB in patients residing in California. METHODS: Serological testing for reactivity to Bb and RFB antigens was performed in 543 patients with suspected tick-borne illness using a Western blot technique. Further evaluation of a subset of 321 patients residing in California was obtained. Serum samples were tested for IgM and IgG antibodies reactive with Bb and RFB, and samples were classified by county of residence according to Bb reactivity alone, RFB reactivity alone, and dual reactivity against Bb and RFB. Seroreactivity was ranked in counties with the highest absolute number and the highest prevalence of positive samples. RESULTS: Of the 543 total serum samples, 32% were positive for Bb, 22% were positive for RFB, and 7% were positive for both Bb and RFB. Of the 321 serum samples from patients residing in California, 33% were positive for Bb, 27% were positive for RFB, and 11% were positive for both Bb and RFB. In the California cohort, the highest rates of positive serological testing for Bb were found in Santa Clara, Alameda, and Contra Costa counties, while the highest rates of positive serological testing for RFB were found in Santa Clara, Alameda, Marin, and San Francisco counties. The highest rates of dual reactivity against Bb and RFB were found in Contra Costa, Alameda, and San Francisco counties. Among the 24 counties with patients who were tested, Bb seropositivity alone was found in four counties, RFB seropositivity alone was found in two counties, and seropositivity for both Bb and RFB was found in 14 counties. CONCLUSION: Results of this pilot study suggest that seroreactivity against Bb and RFB is widespread in California, and dual exposure to Bb and RFB may complicate the diagnosis of tick-borne disease. Greater awareness of RFB and broader screening for this tick-borne infection is warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".