Atmospheric hydrogen peroxide and Eoarchean iron formations
Bibliographic record
Abstract
It is widely accepted that photosynthetic bacteria played a crucial role in Fe(II) oxidation and the precipitation of iron formations (IF) during the Late Archean-Early Paleoproterozoic (2.7-2.4 Ga). It is less clear whether microbes similarly caused the deposition of the oldest IF at ca. 3.8 Ga, which would imply photosynthesis having already evolved by that time. Abiological alternatives, such as the direct oxidation of dissolved Fe(II) by ultraviolet radiation may have occurred, but its importance has been discounted in environments where the injection of high concentrations of dissolved iron directly into the photic zone led to chemical precipitation reactions that overwhelmed photooxidation rates. However, an outstanding possibility remains with respect to photochemical reactions occurring in the atmosphere that might generate hydrogen peroxide (H2 O2 ), a recognized strong oxidant for ferrous iron. Here, we modeled the amount of H2 O2 that could be produced in an Eoarchean atmosphere using updated solar fluxes and plausible CO2 , O2 , and CH4 mixing ratios. Irrespective of the atmospheric simulations, the upper limit of H2 O2 rainout was calculated to be <10(6) molecules cm(-2) s(-1) . Using conservative Fe(III) sedimentation rates predicted for submarine hydrothermal settings in the Eoarchean, we demonstrate that the flux of H2 O2 was insufficient by several orders of magnitude to account for IF deposition (requiring ~10(11) H2 O2 molecules cm(-2) s(-1) ). This finding further constrains the plausible Fe(II) oxidation mechanisms in Eoarchean seawater, leaving, in our opinion, anoxygenic phototrophic Fe(II)-oxidizing micro-organisms the most likely mechanism responsible for Earth's oldest IF.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".