Bibliographic record
Abstract
If genome space is finite with little, if any, DNA that is not functional under some circumstance , then potential conflicts between different forms of genomic information must be resolved by appropriate trade-offs. These trade-offs sometimes require that genes accommodate spacers, introns, and simple sequence elements. The nature and extent of the trade-offs varies with the biological species. Study of trade-offs is facilitated in genes or species where demands are exceptional (e.g. genes under positive selection pressure to adapt proteins, genes that overlap, and species under extreme downward or upward GC -pressures). Spacers and introns are likely to have existed early in evolution because they are preferential sites for the stem-loop structures that are necessary for initiating recombination and, hence, error-detection and correction. Genes, as recognized today, would have arisen in sequences already adapted for these purposes. Purine-loading pressure would have supported protein-pressure in provoking the splitting into introns of what might otherwise have been large exons. From this perspective we can understand why the genes of the malaria parasite are extraordinarily long, and we can identify the potential Achilles heel of the AIDS virus as the dimer-linkage sequence that is essential for the copackaging of disparate genomes, so allowing recombination repair in a future host. 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.020 |
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".