Bibliographic record
Abstract
West Nile virus in the United States West Nile virus (WNV) has been detected in the United States each year since 1999. In several eastern states, like New York, WNV has become well-established and human and animal cases are expected each summer. WNV has spread westward in recent years and most confirmed cases in 2006 occurred in residents of states west of Mississippi. With nearly 1,000 cases, Idaho reported almost a quarter of all cases in the nation in 2006.1 Numbers of reported human WNV cases have become a less reliable indicator of overall disease burden in many states. This is evidenced by the state-to-state variation in the ratio of neuroinvasive disease to West Nile fever cases that suggests testing in endemic states has declined overall and the majority of confirmed cases have severe illness. WNV surveillance in Alaska Surveillance for WNV in Alaska began in 2002 when the Alaska State Virology Laboratory (ASVL) developed capacity to test both avian and human specimens for evidence of WNV infection. Since then, there has been no evidence of locally-occurring WNV infection in either humans or animals. 2006 results – Birds For the 2006 season, there were 33 birds tested for WNV at ASVL; all were negative. The majority of birds tested were either corvids or raptors (Table).
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.388 | 0.289 |
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".