Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Viruses are ubiquitous in the sea and appear to outnumber all other forms of marine life by at least an order of magnitude. Through selective infection, viruses influence nutrient cycling, community structure, and evolution in the ocean. Over the past 20 years we have learned a great deal about the diversity and ecology of the viruses that constitute the marine virioplankton, but until recently the emphasis has been on DNA viruses. Along with expanding knowledge about RNA viruses that infect important marine animals, recent isolations of RNA viruses that infect single-celled eukaryotes and molecular analyses of the RNA virioplankton have revealed that marine RNA viruses are novel, widespread, and genetically diverse. Discoveries in marine RNA virology are broadening our understanding of the biology, ecology, and evolution of viruses, and the epidemiology of viral diseases, but there is still much that we need to learn about the ecology and diversity of RNA viruses before we can fully appreciate their contributions to the dynamics of marine ecosystems. As a step toward making sense of how RNA viruses contribute to the extraordinary viral diversity in the sea, we summarize in this review what is currently known about RNA viruses that infect marine organisms.
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.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.018 |
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 it