16S rRNA gene sequences of Candidatus Methylumidiphilus (Methylococcales), a putative methanotrophic genus in lakes and ponds
Bibliographic record
Abstract
A putative novel methanotrophic genus, Candidatus Methylumidiphilus ( Methylococcales) , was recently shown to be ubiquitous and one of the most abundant methanotrophic genera in water columns of oxygen-stratified lakes and ponds in boreal and subarctic areas. However, it has probably escaped detection in many previous studies that used 16S rRNA gene amplicon sequencing due to insufficient database coverage, as previously analysed metagenome-assembled genomes (MAGs) affiliated with Ca . Methylumidiphilus do not contain 16S rRNA genes. Therefore, we screened MAGs affiliated with the genus for their 16S rRNA gene sequences in a recently published lake and pond MAG data set. Among 66 MAGs classified as Ca . Methylumidiphilus (with completeness over 40% and contamination less than 5%) originating from lakes in Finland, Sweden and Switzerland as well as from ponds in Canada, we found 5 MAGs, each containing one 1532 bp sequence spanning the V1-V9 regions of the 16S rRNA gene. After removal of sequence redundancy, this resulted in 2 unique 16S rRNA gene sequences. These sequences represented 2 different putative species: Ca. Methylumidiphilus alinenensis (GenBank accession OK236221) and another unnamed species of Ca . Methylumidiphilus (GenBank accession OK236220). We suggest that including these 2 sequences in reference databases will enhance 16S rRNA gene-based detection of members of this genus from environmental samples.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".