Revisiting the Relationship between Weather and Interannual Variation in Human Plague Cases in the Southwestern United States
Bibliographic record
Abstract
Plague is a rare, potentially fatal flea-borne zoonosis endemic in the western United States. A previous model described interannual variation in human cases based on temperature and lagged precipitation. We recreated this model in northeastern Arizona (1960-1997) to evaluate its capacity to predict recent cases (1998-2022). In recreating the original model, we found that future instead of concurrent temperature had inadvertently been used for the presented fit. Prediction from our revised models with lagged precipitation and temporally plausible temperature relationships aligned with low observed cases in 1998-2022. Elevated precipitation associated with high cases in historical data (>6 inches combined precipitation over two previous springs) was only observed once in the last quarter century, so we could not assess if these conditions were reliably associated with elevated (four or more) human plague cases. Observed weather conditions were similar to those previously associated with low (fewer than or equal to two) case counts, suggesting "baseline" conditions in the last quarter century.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".