Bibliographic record
Abstract
Over 40% of mammalian genomes comprise the products of reverse transcription. Among such retrotransposed sequences are those characterized by the presence of long terminal repeats (LTRs), including the endogenous retroviruses (ERVs), which are inherited genetic elements closely resembling the proviruses formed following exogenous retrovirus infection. Sequences derived from ERVs make up at least 8 to 10% of the human and mouse genomes and range from ancient sequences that predate mammalian divergence to elements that are currently still active. In this chapter we describe the discovery, classification and origins of ERVs in mammals and consider cellular mechanisms that have evolved to control their expression. We also discuss the negative effects of ERVs as agents of genetic disease and cancer and review examples of ERV protein domestication to serve host functions, as in placental development. Finally, we address growing evidence that the gene regulatory potential of ERV LTRs has been exploited multiple times during evolution to regulate genes and gene networks. Thus, although recently endogenized retroviral elements are often pathogenic, those that survive the forces of negative selection become neutral components of the host genome or can be harnessed to serve beneficial roles.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.009 |
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".