“Freezing” Thermophiles: From One Temperature Extreme to Another
Bibliographic record
Abstract
New detections of thermophiles in psychrobiotic (i.e., bearing cold-tolerant life forms) marine and terrestrial habitats including Arctic marine sediments, Antarctic accretion ice, permafrost, and elsewhere are continually being reported. These microorganisms present great opportunities for microbial ecologists to examine biogeographical processes for spore-formers and non-spore-formers alike, including dispersal histories connecting warm and cold biospheres. In this review, we examine different examples of thermophiles in cryobiotic locations, and highlight exploration of thermophiles at cold temperatures under laboratory conditions. The survival of thermophiles in psychrobiotic environments provokes novel considerations of physiological and molecular mechanisms underlying natural cryopreservation of microorganisms. Cultures of thermophiles maintained at low temperature may serve as a non-sporulating laboratory model for further exploration of metabolic potential of thermophiles at psychrobiotic temperatures, as well as for elucidating molecular mechanisms behind natural preservation and adaptation to psychrobiotic environments. These investigations are highly relevant for the search for life on other cold and icy planets in the 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".