Phylotyper: <i>in silico</i> predictor of gene subtypes
Bibliographic record
Abstract
SUMMARY: Whole genome sequencing (WGS) is being adopted in public health for improved surveillance and outbreak analysis. In public health, subtyping has been used to infer phenotypes and distinguish bacterial strain groups. In silico tools that predict subtypes from sequences data are needed to transition historical data to WGS-based protocols. Phylotyper is a novel solution for in silico subtype prediction from gene sequences. Designed for incorporation into WGS pipelines, it is a general prediction tool that can be applied to different subtype schemes. Phylotyper uses phylogeny to model the evolution of the subtype and infer subtypes for unannotated sequences. The phylogenic framework in Phylotyper improves accuracy over approaches based solely on sequence similarity and provides useful contextual feedback. AVAILABILITY AND IMPLEMENTATION: Phylotyper is a python and R package. It is available from: https://github.com/superphy/insilico-subtyping. CONTACT: matthew.whiteside@phac-aspc.gc.ca. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".