Terrestrial iron biosignatures and their potential in solar system exploration for astrobiology
Bibliographic record
Abstract
Iron (Fe) is one of the most abundant elements in the solar system. It plays an important role in life by participating in redox reactions for energy generation (e.g. , by Fe(II)-oxidizing and Fe(III)-reducing microorganisms) and as a cofactor in multiple assimilatory metabolisms (e.g. , DNA replication). Fe-metabolizing microorganisms are ubiquitous on Earth, from soils and sediments to deep-sea hydrothermal vents. They catalyze Fe redox transformations between its most common redox species Fe(II) and Fe(III), and couple this to carbon degradation, CO 2 fixation, nitrate reduction and photosynthesis, thus linking the biogeochemical cycles of Fe with carbon and nitrogen. Biogenic Fe (oxyhydr)oxide minerals (BIOS), i.e. the products of neutrophilic Fe(II)-oxidizing microorganisms, are biosignatures of interest on Earth and potentially on other habitable bodies in our solar system, such as Mars and icy moons. Here, we review the habitats, mechanisms, products and preservation of Fe-metabolizing microorganisms on Earth. We translate this knowledge into a biosignature context for the search of potential Fe-metabolizing microorganisms in the solar system.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".