Bibliographic record
Abstract
Large DNA viruses, such as poxviruses, encode an array of gene products, both secreted and intracellular, that systematically debilitate the various host responses to virus infection. The primary targets of the secreted gene products are members of the inflammatory innate immune system, such as the interferons, tumor necrosis factors, diverse interleukins, complement and the chemokine pathways. Poxvirus-infected cells also maintain a low profile to escape the cell-mediated arm of the adaptive immune response. Virulence factors that mediate this ‘virostealth’ are generally expressed intracellularly and interfere with host signaling processes or antigen presentation. Poxviruses also interfere with the cellular apoptotic response by regulating several key checkpoints within the cell. While many poxvirus virulence factors exhibit some sequence relationship with host proteins, suggesting that these genes may have been acquired from an ancestral host, others show no obvious similarity to any known host genes. Due to the intimate nature of the coevolution with their hosts, poxviral immunomodulators have proved useful in examining diverse aspects of immunology, virology and cell biology. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".