Bibliographic record
Abstract
Secondary metabolites generally benefit their producers as poisons that protect them against competitors, predators or parasites. They are produced from universally present precursors (most often acetyl-CoA, amino acids or shikimate) by specific enzymes that probably arose by the duplication and divergence of genes originally coding for primary metabolism. Most secondary metabolites are restricted to single major taxa on the universal phylogenetic tree and so probably originated only once. But different secondary metabolic pathways have originated from different ancestral enzymes at radically different times in evolution. Secondary metabolites are most abundantly produced by microorganisms in crowded habitats and by plants, fungi and sessile animals like sponges, where chemical defence and attack rather than physical escape or fighting are at a premium. The first secondary metabolites were probably antibiotics produced in microbial mats over 3500 million years ago. These first ecosystems probably consisted entirely of eubacteria: archaebacteria and eukaryotes arose much later. As a phylogenetic context for considering the earliest origins of antibiotics I summarize a cladistic analysis of the explosive eubacterial primary diversification. This suggests that the most primitive surviving cells are the photosynthetic heliobacteria. Study of these and of the nearly as primitive chloroflexibacteria, spirochaetes and deinobacteria may provide the best evidence on the origins of secondary and primary metabolism.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".