The canine oral microbiome: variation in bacterial populations across different niches
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Microbiota from different niches within the canine oral cavity were profiled and compared. Supragingival plaque and stimulated saliva, were collected alongside samples from the buccal and tongue dorsum mucosa, from 14 Labrador retrievers at three timepoints within a 1 month timeframe. The V3-V4 region of the 16S rRNA gene was sequenced via Illumina MiSeq. RESULTS: Supragingival plaque microbiota had the highest bacterial diversity and the largest number of significant differences in individual taxa when compared to the other oral niches. Stimulated saliva exhibited the highest variability in microbial composition between dogs, yet the lowest bacterial diversity amongst all the niches. Overall, the bacteria of the buccal and tongue dorsum mucosa were most similar. CONCLUSIONS: The bacterial community profiles indicated three discrete oral niches: soft tissue surfaces (buccal and tongue dorsum mucosa), hard tissue surface (supragingival plaque) and saliva. The ability to distinguish the niches by their microbiota signature offers the potential for microbial biomarkers to be identified in each unique niche for diagnostic use.
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.
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) | 0.001 | 0.001 |
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 it