Enzyme nomenclature and classification: the state of the art
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The IUBMB enzyme classification system, available at the IUBMB ExplorEnz website, uses a four-component number (the EC number) that identifies an enzyme in terms of reaction catalysed. There were originally six recognized groups of enzymes: Oxidoreductases (EC 1), Transferases (EC 2), Hydrolases (EC 3), Lyases (EC 4), Isomerases (EC 5) and Ligases (EC 6). Of these, the lyases, which are defined as 'enzymes that cleave C-C, C-O, C-N and other bonds by means other than by hydrolysis or oxidation', present particular recognition and classification problems. Recently, a new class, the Translocases (EC 7), has been added, which incorporates enzymes that catalyse the movement of ions or molecules across membranes or their separation within membranes. A new subclass of the isomerases has also been included for those enzymes that alter the conformations of proteins and nucleic acids. Newly reported enzymes are being regularly added to the list after validation and where new information affects the classification of an existing entry, a new EC number is created, but the old one is not reused.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it