Bibliographic record
Abstract
How life emerged on this planet is one of the most important and fundamental questions of science.Although nearly all details concerning our origins have been lost in the depths of time, there is compelling evidence to suggest that the earliest life might have exploited the catalytic and self-recognition properties of RNA to survive.If an RNA based replicating system could be constructed in the laboratory, it would be much easier to understand the challenges associated with the very earliest steps in evolution and provide important insight into the establishment of the complex metabolic systems that now dominate this planet.Recent progress into the selection and characterization of ribozymes that promote nucleotide synthesis and RNA polymerization are discussed and outstanding problems in the field of RNA-mediated RNA replication are summarized.C ell division is a fundamental biological process in which genetic information is duplicated and shared between daughter cells.In extant cellular life, DNA serves as the repository of genetic information, but its replication is complicated by the daunting size and complex structural organization of modern genomes.For this reason, multiple enzymes are required to ensure faithful genomic replication in all higher life forms.Notably, simpler replicating systems such as viruses, have smaller genomes and tend to use correspondingly more errorprone replicative machinery (Kunkel and Bebenek 2000;Gago, Elena et al. 2009).Presumably, if the initial organisms on this planet also had small genomes, then the earliest genomic replication could have been a relatively simple and error-prone process compared with the complex replicative strategies of modern life.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".