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Terrestrial iron biosignatures and their potential in solar system exploration for astrobiology

2025· article· en· W4415769274 on OpenAlex
Laura I. Tenelanda-Osorio, Andreas Kappler, Muammar Mansor

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEarth-Science Reviews · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsInnovation Cluster (Canada)
FundersEberhard Karls Universität TübingenDeutsche Forschungsgemeinschaft
KeywordsSolar SystemAsteroidAtmosphere (unit)PlanetTerrestrial planet

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.795
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.250
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it