Rare unclassified 16S rRNA operational taxonomic units from the uncharted Engaño Bay (Argentinean Patagonia)
Bibliographic record
Abstract
Rare microbes make up most of the diversity of marine microbiomes, and recent works have highlighted their importance for microbial community dynamics and in fragmented habitats. Rare taxa have been infrequently studied in comparison with abundant groups, and rare unclassified sequences are common in culture-independent studies. Here, we describe a detailed analysis of nonclassifiable sequences from the Chubut river estuary at the Argentinean Patagonia. Standard taxonomic assignments of environmental 16S rRNA sequences resulted in about 13% unclassified operational taxonomic units (OTUs). The potential affiliations of these OTUs could be narrowed by mapping the classification software assignments on a phylogeny obtained directly from our environmental sequence data. Customized BLAST analyses were remarkably consistent with these phylogenetic assignments, especially when the unclassified OTUs were blasted against sequences from cultured and type microorganisms. In addition, our BLAST analyses revealed significant similarities between several unclassified OTUs and a plethora of unclassified sequences from around the world. Further phylogenetic comparisons with 6194 carefully selected reference sequences showed that these unclassified sequences may correspond to 5 unnamed groups, possibly encompassing ranks from subclass to family inside the Alphaproteobacteria, and to an unknown Gracilibacteria lineage. Overall, these results demonstrate the value of straight phylogenetic analysis, customized BLAST searches, and comparisons with sequences from type material, for the systematic study of rare unclassified sequences.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".