maureenjcohen/ExoPlaSim: New haze optical data and tutorial
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.
Bibliographic record
Abstract
The PlaSim 3D general climate model, extended for terrestrial planets. This model contains the PlaSim GCM, as well as all necessary modifications to run tidally-locked planets, planets with substantially different surface pressures than Earth, planets orbiting stars with different effective temperatures, super-Earths, and more. This model also includes the ability to compute carbon-silicate weathering, dynamic orography through the glacier module (though only accumulation and ablation/evaporation/melting are included; glacial flow and spreading are not), and storm climatology. Future features will include support for multiple celestial light sources (e.g. for a habitable moon orbiting a Jovian planet, or circumbinary planets), coupling with N-body integrators such as REBOUND, and CO2 condensation. This release includes photochemical haze/dust transport and radiative transfer. Transport and radiative transfer schemes are described in "Haze optical depth in exoplanet atmospheres varies with rotation rate: Implications for observations," Cohen et al. (2024). Includes optical haze constants with corrected backscattering efficiencies, calculated based on data provided in He et al. 2023 and Corrales et al. 2023 for the stellar spectra of TRAPPIST-1 and Wolf 1061. A tutorial has been added demonstrating how to use the aerosol module, including references to the data sources.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.022 |
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 it