Bibliographic record
Abstract
Abstract A protein‐coding gene is composed of a series of nucleotide triplets – the codons – that encrypt not only the protein content but also the start and stop signals. There are 64 (4 3 ) codons in the canonical genetic code, which encode 20 amino acids with redundancy. Hence, there are synonymous codons that encode the same amino acids, and they are used at different frequencies among different species. The resultant codon‐usage biases reveal complex interplays of mutation and selection. Protein‐coding genes can be organised into families of similar function, structure and sequence, according to their shared evolutionary histories. Individual proteins are modularly constructed of domains, which are often rearranged on evolutionary timescales to create functionally novel proteins. Key Concepts: A protein‐coding gene consists of a series of nucleotide triplets. The genetic code defines the relationship between codons and amino acids. The genetic code can be organised into two halves and four quarters, which manifest distinct physiochemical features. Codon usage bias, a phenomenon in which synonymous codons (encoding the same amino acid) are used at different frequencies in different species, is a result of complex interplays between mutation and selection. Protein‐coding genes are organised into families of similar function, structure and sequence, according to their shared evolutionary histories. Individual proteins are modularly constructed from domains, which are often rearranged on evolutionary timescales to create functionally novel proteins.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.317 | 0.317 |
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".