CAMEMBERT: A Mini-Neptunes General Circulation Model Intercomparison
Bibliographic record
Abstract
With observatories such as JWST, astronomers are now attempting to better understand the previously inscrutable atmospheres of mini-Neptunes, the smaller and often cooler cousins of the better-studied hot Jupiters. General circulation models (GCMs) are an essential part of the toolset used to improve that understanding, from both the perspective of theoretical investigations and in support of observation. It is only recently, however, that the exoplanet community has begun to benchmark and study the behaviour of our GCMs through intercomparisons, a practice that has been going on in the Earth sciences community for decades. With that in mind, we present CAMEMBERT (Comparing Atmospheric Models of Extrasolar Mini-Neptunes Building and Envisioning Retrievals and Transits), a community effort to compare the many of the GCMs used in studies of mini-Neptunes using common parameters and targets in hopes to better understand differences between our models and to better inform the interpretations of our results. This talk will cover the protocol as well as preliminary insights from the project. CAMEMBERT is a part of the CUISINES meta-framework, which also includes the THAI, SAMOSA, CREME, and MOCHA GCM intercomparisons.
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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 | 0.003 |
| 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 | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".