Data from: The molecular phylogeny of Chionaster nivalis reveals a novel order of psychrophilic and globally distributed Tremellomycetes (Fungi, Basidiomycota)
Bibliographic record
Abstract
Snow and ice present challenging substrates for cellular growth, yet microbial snow communities not only exist, but are diverse and ecologically impactful. These communities are dominated by green algae, but additional organisms, such as fungi, are also abundant and may be important for nutrient cycling, syntrophic interactions, and community structure in general. However, little is known about these non-algal community members, including their taxonomic affiliations. An example of this is Chionaster nivalis, a unicellular fungus that is morphologically enigmatic and frequently observed in snow communities globally. Despite being described over one hundred years ago, the phylogeny and higher-level taxonomic classifications of C. nivalis remain unknown. Here, we isolated and sequenced the internal transcribed spacer (ITS) and the D1-D2 region of the large subunit ribosomal RNA gene of C. nivalis, providing a molecular barcode for future studies. Phylogenetic analyses using the ITS and D1-D2 region revealed that C. nivalis is part of a novel lineage in the class Tremelomycetes (Basidiomycota, Agaricomycotina) for which a new order, Chionasterales ord. nov. (MB838717), and family, Chionasteraceae fam. nov. (MB838718), are proposed. Comparisons between C. nivalis and sequences generated from environmental surveys revealed that the Chionasterales are globally distributed and probably psychrophilic, as they appear to be limited to the high alpine and arctic regions. These results highlight the unexplored diversity that exists within these extreme habitats and emphasize the utility of single-cell approaches in characterizing these complex algal-dominated communities.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".