AVIAN VACUOLAR MYELINOPATHY OUTBREAKS AT A SOUTHEASTERN RESERVOIR
Bibliographic record
Abstract
Avian vacuolar myelinopathy (AVM) is a neurologic disease of unknown etiology that affects bald eagles (Haliaeetus leucocephalus), American coots (Fulica americana), and several species of waterfowl. An unidentified neurotoxin is suspected as the cause of AVM, which has been documented at several reservoirs in the southeastern United States. We conducted diagnostic and epidemiologic studies annually during October-March from 1998-2004 at Clarks Hill/Strom Thurmond Lake on the Georgia/South Carolina border to better understand the disease. Avian vacuolar myelinopathy was confirmed or suspected as the cause of morbidity and mortality of 28 bald eagles, 16 Canada geese (Branta canadensis), six American coots, two great-horned owls (Bubo virginianus), and one killdeer (Charadrius vociferus). Active surveillance during the outbreaks yielded annual average prevalence of vacuolar lesions in 17-94% of coots, but not in 10 beavers (Castor canadensis), four raccoons (Procyon lotor), and one gray fox (Urocyon cinereoargenteus) collected for the study. Brain lesions were not apparent in 30 Canada geese collected and examined in June 2002. The outbreaks at this location from 1998-2004 represent the most significant AVM-related bald eagle mortality since the Arkansas epornitics of 1994-95 and 1996-97, as well as the first confirmation of the disease in members of Strigiformes and Charadriiformes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".