Phylogenomic grouping of <i>Listeria monocytogenes</i>
Bibliographic record
Abstract
The precise delineation of lineages and clonal groups are a prerequisite to examine within-species genetic variations, particularly with respect to pathogenic potential. A whole-genome-based approach was used to subtype and subgroup isolates of Listeria monocytogenes. Core-genome typing was performed, employing 3 different approaches: total core genes (CG), high-scoring segment pairs (HSPs), and average nucleotide identity (ANI). Examination of 113 L. monocytogenes genomes available in-house and in public domains revealed 33 phylogenomic groups (PGs). Each PG could be differentiated into a number of genomic types (GTs), depending on the approach used: HSPs (n = 57 GTs), CG (n = 71 GTs), and ANI (n = 83 GTs). Demarcation of the PGs was concordant with the 4 known lineages and led to the identification of sublineages in the lineage groups I, II, and III. In addition, PG assignments had discriminatory power similar to multi-virulence-locus sequence typing types and clonal complexes of multilocus sequence typing. Clustering of genomically highly similar isolates from different countries, sources, and isolation dates using whole-genome-based PG suggested that dispersion of phylogenomic clones of L. monocytogenes preceded their subsequent evolution. Classification according to PG may act as a guideline for future epidemiological studies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".