The Molecular Record of Metabolic Activity in the Subsurface of the Río Tinto Mars Analog
Bibliographic record
Abstract
In the subsurface, the interplay between microbial communities and the surrounding mineral substrate, potentially used as an energy source, results in different mineralized structures. The molecular composition of such structures can record and preserve information about the metabolic pathways that have produced them. To characterize the molecular composition of the subsurface biosphere, we have analyzed some core samples by time-of-flight secondary ion mass spectrometry (ToF-SIMS) that were collected in the borehole BH8 during the operations of the Mars Analog and Technology Experiment (MARTE) project. The molecular analysis at a micron-scale mapped the occurrence of several inorganic complexes bearing PO 3 - , SO x (2 to 4) - , NO x (2,3) - , FeO x (1,2) - , SiO 2 - , and Cl - . Their distribution correlates with organic molecules that were tentatively assigned to saturated and monounsaturated fatty acids, polyunsaturated fatty acids, saccharides, phospholipids, sphingolipids, and potential peptide fragments. SO x - appear to be mineralizing some microstructures larger than 25 microns, which have branched morphologies, and that source SO 3 -bearing adducts. PO 3 -rich compounds occur in two different groups of microstructures which size, morphology, and composition are different. While a group of >40-micron sized circular micronodules lacks organic compounds, an ovoidal microstructure is associated with m/z of other lipids. The NO 2 - /NO 3 - and Cl - ions occur as small microstructure clusters (<20 microns), but their distribution is dissimilar to the mineralized microstructures bearing PO 3 - , and SO 3 - . However, they have a higher density in areas with more significant enrichment in iron oxides that are traced by different Fe-bearing anions like FeO 2 - . The distribution of the organic and inorganic negative ions, which we suggest, resulted from the preservation of at least three microbial consortia (PO 4 - -, and NO 2 - -/NO 3 - -mineralizers PO 4 -lipid bearing microstructures), would have resulted from different metabolic and preservation pathways.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".