Additional file 7 of MetaPro: a scalable and reproducible data processing and analysis pipeline for metatranscriptomic investigation of microbial communities
Bibliographic record
Abstract
Additional file 7: Table S3.Read annotation statistics for NOD mouse datasets from MetaPro, HUMAnN3, HUMAnN2, SAMSA2 compared with the gold standard. This table shows the number of reads in each NOD mouse sample each pipeline assigned to the 8 ASF bacteria: Clostridium ASF356, Clostridium ASF502, Eubacterium plexicaudatum, Firimicutes ASF500, Lactobacillus ASF360, Lactobacillus murinus, Mucisprillim schaedleri, and Parabacteroides ASF519. Due to the similarity between P. ASF519, and P. goldsteinii, the pipelines will sometimes annotate to P. goldsteinii rather than to P.ASF519. P. goldsteinii was also a dominant species found within the samples outside of the 8 ASF bacteria. The expected results were produced by annotating the reads with a reference containing only the 8 ASF, using BWA.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.291 | 0.124 |
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".