Additional file 3 of Compositional analysis of the tonsil microbiota in relationship to Streptococcus suis disease in nursery pigs in Ontario
Bibliographic record
Abstract
Additional file 3. Table S1: Total number of pigs before and after data quality filtering. Confirmed cases are pigs that showed clinical signs of S. suis infection and S. suis was found in the systemic sites such as blood, meninges, and/or spleen. Probable cases are pigs that showed clinical signs of S. suis infection but S. suis was not found in the any systemic site. Healthy controls are pigs without clinical signs of S. suis infection. *Samples that were excluded during the rarefying process. Table S2: Non phylogenetics alpha diversity (Observed, Shannon metrics), Reads per sample and phylogenetics (PD) Diversity matrix among the 57 rarefied samples from 18 confirmed, 17 healthy, and 22 probable cases. Table S3: Taxonomic contributions to Dirichlet multinomial mixture (DMM) model components identifying the important taxa that drivers the variances across the samples. Table S4: Top ASVs that are differently abundant between the two DMM community types as identified by ANCOM-BC.
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.
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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.759 | 0.083 |
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".