Surface mineral crusts: a potential strategy for sampling for evidence of life on Mars
Bibliographic record
Abstract
Abstract Surface mineral crusts on Earth are highly diverse and usually, contain microbial life. Crusts constitute an attractive target to search for life: they require water for their formation, they efficiently entrap organic matter and are relatively easy to sample and process. They hold a record of life in the form of microbial remains, biomolecules and carbon isotope composition. A miniaturized Raman spectrometer is included in the ExoMars 2020 payload as it is sensitive to a range of photosynthetic pigments. Samples from the Haughton Impact Structure, Canadian High Arctic and others, shows the preservation of pigments in a range of crust types, especially supra-permafrost carbonate crusts and cryptogamic crusts. The Raman spectral signatures of these crusts are shown along with biomarker analysis to showcase these techniques prior to the ExoMars 2020 mission. Carotenoids and other photoprotective microbial pigments are identified in the Haughton surface crusts using Raman spectroscopy. Gas chromatography-mass spectrometry analyses show a distribution of fatty acids which are most likely from a cyanobacterial source. The successful demonstration of these analyses in the Haughton Impact structure shows the biosignature of surface mineral crusts can be easily extracted and provides an excellent target for sampling evidence 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".