The Spread of Endogenous Retroviruses in Populations Infected by Exogenous Viruses
Bibliographic record
Abstract
Retroviruses insert DNA copies of themselves into the chromosomes of their hosts forming proviruses that can synthesize new transmissible viruses. Exogenous retroviruses (XRVs) insert into the DNA of somatic cells and are transmitted infectiously. Endogenous retroviruses (ERVs) become inserted in the DNA of germline cells and are transmitted genetically. ERVs can spread through the genome by transposition. ERVs originate from an initial copy of an XRV inserted into the genome of an organism infected by the XRV. Many XRVs are transmitted maternally as well as horizontally; therefore, we consider the effect of maternal transmission on the evolution of virulence of an XRV. Our model shows that the XRV either evolves high virulence with low maternal transmission, or vice versa. We then consider the spread of ERV genes in conjunction with the infectious spread of an XRV. Beginning from a single copy of an ERV, we calculate the probability that it spreads to fixation (i.e., the state where all individuals contain ERV genes). This depends on its virulence and transposition rate. If the XRV is present, the fixation probability also depends on the virulence of the XRV and whether the ERV provides resistance to the XRV. An ERV with only a small deleterious effect on host fitness has a high fixation probability, particularly if it provides resistance to the XRV. We also show that, if an ERV does not spread to fixation, it can still cause elimination of the XRV, with the end result that the population is cleared of both XRV and ERV.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".