Supplementary data for "Atmospheric dynamics of first steps toward terraforming Mars", by Richardson et al.
Bibliographic record
Abstract
Supplementary data for "Atmospheric dynamics of first steps toward terraforming Mars", by Richardson et al. Mars-configured planetWRF (MarsWRF) output are included for: the steady-state reference run (wrfout_ref.nc), the steady-state Al n60 equatorial release case (wrfout_equat_al_n60.nc); and, the steady-state graphene n15 equatorial release case (wrfout_equat_c_n15.nc). Output are at for four times per Sol, for each of the 669 Sols in the model year. Data is in NetCDF format. It can be processed with NCO/NCKS tools, viewed with NcView, and libraries to access NetCDF files are widely available for Python, Fortran, and other languages. The header, variables list, and attributes can be seen by running "ncdump -h" on the files (after ungzipping them). Note the NetCDF files include many of the MarsWRF model constants and parameters as NetCDF global attributes. The files were compressed with "gzip " and should be uncompressed using "gunzip .gz". Because of difficulties uploading multi-GB files, each have been split into four smaller files on the basis of output timestep (669 records, or one quarter of the year, each). They can be reassembled using "ncrcat" after they have been uncompressed. planetWRF namelist.input files for each run (readable in any text editor) are included along with a restart file common to all runs in this experiment set (NetCDF file: wrfrst...). For reference, the simulations were conducted with code at git commit 855feebb85 Text files are included containing the radiative properties for each manufactured particle type used in the simulations. Contact authors for more information. https://www.planetwrf.com
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.693 | 0.285 |
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".