Cryomicrobial Ecology: Still Much To Learn about Life Left Out in the Cold
Bibliographic record
Abstract
Studies from cryoenvironments on Earth have demonstrated that microbial life is widespread and have identified microorganisms that are metabolically active and can replicate at subzero temperatures if liquid water is present. However, cryophiles (subzero-growing organisms) often exist in low densities in the environment and their growth rate is low, making them difficult to study. Compounding this, a large number of dormant and dead cells are preserved in frozen settings. Using integrated genomic and activity-based approaches is essential to understanding the cold limits of life on Earth, as well as how cryophilic microorganisms are poised to adapt and metabolize in warming settings, such as in thawing permafrost. An increased understanding of cryophilic lifestyles on Earth will also help inform how (and where) we look for potential microbial life on cold planetary bodies in our solar system such as Mars, Europa, and Enceladus.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".