Investigating the oral microbiome in health and periodontal disease
Bibliographic record
Abstract
16S rRNA was used to determine the microbiome associated with health and chronic periodontitis (CP). We hypothesized that a comparison of plaque in health and disease will help identify CP-associated bacteria to develop novel diagnostics for CP. NGS was done against the V3 hypervariable region of the 16S rRNA gene and sequences were clustered based on 97% similarity. Taxonomic assignment and distance measures were used to assess bacterial composition. We identified disease indicators: Filifactor alocis, Synergistes, Tanerella forsythia and TM7 taxa in SupG and SubG sites. Health indicators included Rothia dentocariosa, TM7_7BB428, Selenomonas noxia, Fusobacteriales and Campylobacter. Surprisingly, `classic' periodontal pathogens could be isolated from the tongue in CP patients, which may provide a novel sampling site for prognostic tests. We have identified known periodontal pathogens, including F. alocis, a strong indicator of CP, which could be included as a novel member in the Red complex of periodontal pathogens.
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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 | 0.001 |
| 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 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".