Densovirus associated with sea-star wasting disease and mass mortality
Bibliographic record
Abstract
Populations of at least 20 asteroid species on the Northeast Pacific Coast have recently experienced an extensive outbreak of sea-star (asteroid) wasting disease (SSWD). The disease leads to behavioral changes, lesions, loss of turgor, limb autotomy, and death characterized by rapid degradation ("melting"). Here, we present evidence from experimental challenge studies and field observations that link the mass mortalities to a densovirus (Parvoviridae). Virus-sized material (i.e., <0.2 μm) from symptomatic tissues that was inoculated into asymptomatic asteroids consistently resulted in SSWD signs whereas animals receiving heat-killed (i.e., control) virus-sized inoculum remained asymptomatic. Viral metagenomic investigations revealed the sea star-associated densovirus (SSaDV) as the most likely candidate virus associated with tissues from symptomatic asteroids. Quantification of SSaDV during transmission trials indicated that progression of SSWD paralleled increased SSaDV load. In field surveys, SSaDV loads were more abundant in symptomatic than in asymptomatic asteroids. SSaDV could be detected in plankton, sediments and in nonasteroid echinoderms, providing a possible mechanism for viral spread. SSaDV was detected in museum specimens of asteroids from 1942, suggesting that it has been present on the North American Pacific Coast for at least 72 y. SSaDV is therefore the most promising candidate disease agent responsible for asteroid mass mortality.
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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 | 0.000 | 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".