Antarctic cryptoendolithic bacterial lineages of pre-Cambrian origin as proxy for Mars colonization
Bibliographic record
Abstract
Abstract Cryptoendolithic communities are microbial ecosystems dwelling inside porous rocks. They are able to persist at the edge of the biological potential for life in the ice-free areas of continental Antarctica. These areas include the McMurdo Dry Valleys, often cited as a Terrestrial analog of the Martian environment. Despite their interest as a model for the early colonization by living organisms of terrestrial ecosystems and for adaptation to extreme conditions of stress, little is known about the evolution, diversity and genetic makeup of bacterial species that reside in these environments. We performed metagenomic sequencing of 18 communities from rocks collected in Antarctic desert areas over a distance of about 350 km. A total of 469 draft bacterial genome sequences were assembled, and clustered into 269 candidate species that lack a representative genome in public databases. The majority of these new species belong to monophyletic bacterial clades that diverged from related taxa in a range from 1.2 billion to 410 Ma, much earlier than the glaciation of Antarctica, and that are functionally distinct from known related taxa. The hypothesis that Antarctic cryptoendolithic bacterial lineages were generated by the selection of pre-existing cold-tolerant organisms whose origin dates back to the Tonian glaciations gives new insights for the possibility of life on Mars.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".