Timing of Occurrence of Waterfowl in U.S. Counties and Canadian Counties, Boroughs, Census Districts, and Other Populated Area Designations with Modeled Exposure Status to Highly Pathogenic Avian Influenza Virus in 2021-2022
Bibliographic record
Abstract
This data provides county level occurrence information for all individuals used in modelling potential exposure and spread of highly pathogenic avian influenza (HPAIv) from the 2021-2022 North American outbreak. The data set contains individual identifiers and taxa information, an indicator of exposure, exposure status (Susceptible, Exposed by HPAIv detection in the county, or Exposed by secondary contact with an exposed bird), and date of first occurrence of each individual bird and that bird's exposure status within each visited county. Herein, county refers to any county, parish, borough, census area, or geographic region identified in the associated geospatial data US_CAN_AI.shp (ESRI shapefile format). Occurrence was determined using a spatial join procedure between GPS relocations of individuals and this geospatial dataset.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".