Bibliographic record
Abstract
Abstract Fi.bro.bac.te'ri.a. N.L. masc. n. Fibrobacter type genus of the type order of the class; suff. ‐ ia ending proposed by Gibbons and Murray and by Stackebrandt et al. to denote a class; N.L. neut. pl. n. Fibrobacteria the Fibrobacter class. Taxonomic and Nomenclature Notes According to the List of Prokaryotic names with Standing in Nomenclature (LPSN), the taxonomic status of the class Fibrobacteria is: correct name (last update, April 2026) * . LPSN classification: Bacteria / Pseudomonadati / Fibrobacterota / Fibrobacteria The class Fibrobacteria can also be recovered in the Genome Taxonomy Database (GTDB) as c__Fibrobacteria (version v232) ** . GTDB classification: d__Bacteria / p__Fibrobacterota / c__Fibrobacteria * Freese , H.M. , Meier‐Kolthoff , J.P. , Sardà Carbasse , J. , Afolayan , A.O. , Göker , M. ( 2026 ). TYGS and LPSN in 2025: a Global Core Biodata Resource for genome‐based classification and nomenclature of prokaryotes within DSMZ Digital Diversity. Nucleic Acids Res , 54 (), D884 – D891 ; doi: 10.1093/nar/gkaf1110 ** Parks , D.H. , Chaumeil , P.‐A. , Mussig , A.J. , Rinke , C. , Chuvochina , M. , Hugenholtz , P. ( 2026 ). GTDB release 10: a complete and systematic taxonomy for 715.230 bacterial and 17.245 archaeal genomes. Nucleic Acids Res , 54 (), D743 – D754 ; doi: 10.1093/nar/gkaf1040
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.087 | 0.123 |
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".