Improving diversity in cultures of bacteria from an extreme environment
Bibliographic record
Abstract
The ikaite columns in the Ikka Fjord in Greenland represent one of the few permanently cold and alkaline environments on Earth, and the interior of the columns is home to a bacterial community adapted to these extreme conditions. The community is characterized by low cell numbers imbedded in a calcium carbonate matrix, making extraction of bacterial cells and DNA a challenge and limiting molecular and genomic studies of this environment. To utilize this genetic resource, cultivation at high pH and low temperature was studied as a method for obtaining biomass and DNA from the fraction of this community that would not otherwise be amenable to genetic analyses. The diversity and community dynamics in mixed cultures of bacteria from ikaite columns was investigated using denaturing gradient gel electrophoresis and pyrosequencing of 16S rDNA. Both medium composition and incubation time influenced the diversity of the culture and many hitherto uncharacterized genera could be brought into culture by extended incubation time. Extended incubation time also gave rise to a more diverse community with a significant number of rare species not detected in the initial community.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".