Selective occurrence of <i> <scp>R</scp> hizobiales </i> in frost flowers on the surface of young sea ice near <scp>B</scp> arrow, <scp>A</scp> laska and distribution in the polar marine rare biosphere
Bibliographic record
Abstract
Frost flowers are highly saline ice structures that grow on the surface of young sea ice, a spatially extensive environment of increasing importance in the Arctic Ocean. In a previous study, we reported organic components of frost flowers in the form of elevated levels of bacteria and exopolymers relative to underlying ice. Here, DNA was extracted from frost flowers and young sea ice, collected in springtime from a frozen lead offshore of Barrow, Alaska, to identify bacteria in these understudied environments. Evaluation of the distribution of 16S rRNA genes via four methods (microarray analysis, T-RFLP, clone library and shotgun metagenomic sequencing) indicated distinctive bacterial assemblages between the two environments, with frost flowers appearing to select for Rhizobiales. A phylogenetic placement approach, used to evaluate the distribution of similar Rhizobiales sequences in other polar marine studies, indicated that some of the observed strains represent widely distributed members of the marine rare biosphere in both the Arctic and Antarctic.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".