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
Dynamic virus-host interactions play a critical role in regulating microbial community structure and function. Yet for decades prior to the genomics era, viruses were largely overlooked in microbial ecology research, as only low-throughput culture-based methods of discovering viruses were available. With the advent of metagenomics, culture-independent techniques have provided exciting opportunities to discover and study new viruses. Here, we review recently developed computational methods for identifying viral sequences, exploring viral diversity in environmental samples, and predicting hosts from metagenomic sequence data. Methods to analyze viruses in silico utilize unconventional approaches to tackle challenges unique to viruses, such as vast diversity, mosaic viral genomes, and the lack of universal marker genes. As the field of viral ecology expands exponentially, computational advances have become increasingly important to gain insight into the role viruses in diverse habitats.
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) | 0.001 | 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 | 0.001 |
| 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 it