North American paragonimiasis: epidemiology and diagnostic strategies
Bibliographic record
Abstract
Paragonimiasis is a zoonotic, food-borne trematode infection that affects around 23 million people in Asia, Africa and the Americas. North American paragonimiasis, caused by Paragonimus kellicotti, is a common infection of crustacean-feeding mammals in parts of the USA and Canada. Although infection rates in crayfish are very high in some areas, human infections are rare and depend on the consumption of raw or undercooked crayfish. Human infections can be easily prevented and treated, but proper diagnosis of paragonimiasis is a problem. Paragonimus lung flukes often cause serious disease symptoms before they produce eggs that may be detectable in sputum, bronchoalveolar lavage, stool or histological sections by microscopy or PCR. Antibodies against selected Paragonimus proteins are detectable as early as 2-3 weeks after infection. Therefore, antibody serology is the most promising diagnostic approach for paragonimiasis in North America and elsewhere.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".