Bibliographic record
Abstract
Microorganisms inhabiting terrestrial endolithic habitats are widespread in polar environments including the Antarctic Dry Valleys and the Canadian high Arctic. Their ability to survive in these harsh environments is a result of their finding protection from extremes in temperature, aridity, radiation and winds by colonizing nutrient-rich subsurface habitats that provide more amenable conditions for growth, often developing as vertically stratified communities that include fungi, algae, cyanobacteria and heterotrophic bacteria. Despite finding some refuge from climatic extremes, endolithic microorganisms commonly produce extracellular polysaccharides to avoid desiccation and minimize the damaging effects of freeze-thaw cycles. These microorganisms are geochemically reactive with their endolithic surroundings, observed as heterogeneous concentrations and distributions of metals resulting from mineral dissolution and precipitation reactions as well as element and nutrient release and cycling. Novel microscopy techniques such as SEM-BSE reveal much information about the physiological state of these microorganisms in situ, and show how under specific conditions, microbe-mineral interactions produce unique biosignatures of interest to studies in astrobiology. Their ability to change in situ pH conditions shows that can be directly involved in weathering of endolithic habitats, but the ecology of a given endolithic microbial community can have varying effects on rates of rock weathering. These differences in weathering rates may be an important control on microbial species diversity in polar desert endolithic habitats.
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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 | 0.001 |
| 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".