Model output for "Climate variability leads to multiple oxygenation episodes across the Great Oxidation Event"
Bibliographic record
Abstract
This repository contains all the model output presented in Garduno et al. (2024). Climate variability leads to multiple oxygenation episodes across the Great Oxidation Event. Submitted to Geophysical Research Letters. Model output organization There are seven zip files containing the model output from different simulations described in the main manuscript. See the main manuscript and code repository for more details.: `o2_flux_constant_1.8e12.zip`: model output for simulation in which the O2 input flux is kept constant at a value of 1.8e12 molecules/cm^2/s `o2_flux_constant_2.2e12.zip`: model output for simulation in which the O2 input flux is kept constant at a value of 2.2e12 molecules/cm^2/s `linear_o2_flux_increase.zip`: model output for simulation in which the O2 input flux is linearly increased `linear_o2_flux_increase_change_during_glaciations.zip`: model output for simulation in which the O2 input flux is linearly increased, superimposing a 60% decrease during glaciations and a 60% increase after glaciations. `linear_ri_flux_decrease.zip`: model output for simulation in which the reductant input flux is linearly decreased and the O2 input flux is kept constant `linear_ri_flux_decrease_change_during_glaciations.zip`: model output for simulation in which the reductant input flux is linearly decreased and the O2 input flux is kept constant with a 60% decrease during glaciations and a 60% increase after glaciations. `stability_analysis.zip`: model output for stability analysis of steady states. Each of these folders contains model output every 1e5 years. The files are numbered from 1 to 4998. `1` corresponds to the output at 1e5 years, `2` corresponds to the output at 2e5 years, and so on. There are also files containing the O2 fluxes (`o2_flux.txt`) and reductant input (`ri_flux.txt`) used at each 1e5 output step. Reading data The data files are Fortran binary files. You can read the with the read_evolve_output function implemented in PhotochemPy. You can also use the Python functions provided in the paper's code repository: https://github.com/DanyIvan/climate_goe_over_time/blob/main/read_output.py Names and units The model output files contain the mixing ratios for all modeled species species. They also contain information about: - 'T_time': temperature profile (K) at the output time step.- 'edd_time': eddy diffusivity profile (cm^2/s) at the output time step.- 'press_time': pressure profile (bar) at the output time step.- 'h2osat': saturation vapor pressure profile (bar) at the output time step.- 'time': time (s) at the output time step- 'den': air number density (molecules/cm^3)
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.196 | 0.060 |
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".