Phylogenetic diversity of a microbialite reef in a cold alkaline freshwater lake
Bibliographic record
Abstract
A culture-independent multidomain survey of biodiversity in microbialite structures within the cold alkaline Pavilion Lake (British Columbia, Canada) revealed a largely homogenous community at depths from 10 to 30 m. Real-time quantitative PCR was used to demonstrate that bacteria comprised approximately 80%-95% of recoverable phylotypes. Archaeal phylotypes accounted for <5% of the community in microbialites exposed to the water column, while structures in sediment contact supported 4- to 5-fold higher archaeal abundance. Eukaryal phylotypes were rare and indicated common aquatic diatoms that were concluded not to be part of the microbialite community. Phylogenetic analysis of rRNA genes from clone libraries (N = 491) revealed that alphaproteobacterial phylotypes were most abundant. Cyanobacterial phylotypes were highly diverse but resolved into 4 dominant genera: Acaryochloris, Leptolyngbya, Microcoleus, and Pseudanabaena. Interestingly, microbialite cyanobacteria generally affiliated phylogenetically with aquatic and coral cyanobacterial groups rather than those from stromatolites. Other commonly encountered bacterial phylotypes were from members of the Acidobacteria, with relatively low abundance of the Betaproteobacteria, Chloroflexi, Nitrospirae, and Planctomycetes. Archaeal diversity (N = 53) was largely accounted for by Euryarchaeota, with most phylotypes affiliated with freshwater methanogenic taxa.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".