Photochemical modelling of the climate-redox evolution of the Great Oxidation Event: from a Snowball Earth to a Hot-Moist Greenhouse
Bibliographic record
Abstract
We use an atmospheric one-dimensional photochemical model to investigate the effect of temperature and humidity on the evolution of oxygen and ozone across the Great Oxidation Event (GOE). We model the GOE using fixed surface flux boundary conditions with two scenarios: increasing the oxygen and decreasing the carbon monoxide surface input flux. We find that cold temperatures (<280K) result in oxygen-depleted atmospheres, whereas temperate (280K-310K) and hot (>310K) temperatures result in oxygen-enriched atmospheres after the GOE. Warm and wet climates lead to an increased atmospheric oxidation power through the production of hydrogen oxide radicals, catalyzing the oxidation and depletion of the principal reduced species (methane, carbon monoxide and hydrogen). Consequently, warmer temperatures lead to less oxygen lost through the oxidation of reduced species, resulting in higher oxygen and ozone levels relative to colder temperatures. Therefore, oxygen and ozone can accumulate in the atmosphere faster at warmer temperatures, and the GOE tends to occur at lower oxygen, and higher carbon monoxide, surface input fluxes compared to colder temperatures. However, at temperatures >320K, the abundant water and hydrogen oxide radicals catalyze the depletion of ozone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".