Exploring Methods to Evaluate HPAI Transmission Risk in Iowa During Peak HPAI Incidence, February 2022–December 2023
Bibliographic record
Abstract
Highly pathogenic avian influenza (HPAI), H5N1 strain, began to circulate in the United States on 8 February 2022. The state of Iowa lost the most domestic poultry to HPAI from February 2022–December 2023. This study conducted preliminary evaluations on two environmental risk factors, (inland water surface area, Canada geese abundance) and the availability of the data needed to evaluate them. Higher Canada geese abundance was significantly associated (X2 = 4.29, p = 0.04) with HPAI negative counties. Farm location data were unavailable, limiting our analysis. Van den Broeck et al.’s framework was used to evaluate the available data. Outcome data from Animal and Plant Health Inspection Service (APHIS) had the highest data quality score (11). Canada geese and inland water surface area are predictors worth evaluating, but poultry farm location data are needed for a comprehensive evaluation.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".