Additional file 7 of Revealing the composition of the eukaryotic microbiome of oyster spat by CRISPR-Cas Selective Amplicon Sequencing (CCSAS)
Bibliographic record
Abstract
Additional file 7: Figure S4. Summary of the number of eukaryotic species at each D7 taxonomic level that the sgRNA can cut at the V4 region of the 18S rRNA genes that are flanked by the 18S "universal" primer set TAReuk454FWD1 / TAReukREV3 [54]. These nine sgRNAs, which are among 205242 unique taxon-specific sgRNA designed from the SILVA SSU database (version 119) [80] using CasOligo, are selected to show that some sgRNAs can target more than 1000 species and broad taxonomic groups based on an in-silico analysis (i.e. 100% match to the 18S rRNA gene sequences of the metazoan host at the gRNA-target-site, but no match for protists and fungi). Taxon names on the left side of the panel are shown as SILVA taxonomic hierarchy with levels ranging from D0 (kingdom) to D7. The D7 taxonomic level comprises eukaryotic classes and families.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.824 | 0.191 |
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".