An approximate maximum likelihood phylogenetic tree of sequenced streptomycetes (Nerwick format)
Bibliographic record
Abstract
This is the phylogenetic tree (in Nerwick format) described in the following manuscript submitted to Chemical Science: Formicamycins, antibacterial polyketides produced by Streptomyces formicae isolated from African Tetraponera plant-ants Zhiwei Qin1, John T Munnoch2, Rebecca Devine2, Neil A Holmes2, Ryan F Seipke3, Barrie Wilkinson1* and Matthew I Hutchings2* 1Department of Molecular Microbiology, John Innes Centre, Norwich Research Park, Norwich, NR4 7TJ, United Kingdom. 2School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, United Kingdom. 3School of Molecular and Cellular Biology, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, LS2 9JT, United Kingdom. *Contact: m.hutchings@uea.ac.uk or @matthutchings10 and barrie.wilkinson@jic.ac.uk ESI Figure 4. An approximate maximum likelihood phylogenetic tree of sequenced streptomycetes. A phylogeny was inferred for Mycobacterium tuberculosis and 573 sequenced streptomycetes based on concatenated partial sequences for atpD-rpoB. FastTree local support values are indicated at each node.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.105 | 0.062 |
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".