Functionality of Ice Line Latitudinal EBM Tenacity (FILLET). Protocol Version 1.0. A CUISINES Intercomparison Project
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
Abstract Energy balance models (EBMs) are 1D or 2D climate models that can provide insights into planetary atmospheres, particularly with regard to habitability. Because EBMs are far less computationally intensive than 3D general circulation models (GCMs), they can be run over large uncertain parameter spaces and can be used to explore long-period phenomena, like carbon and Milankovitch cycles. Because horizontal dimensions are incorporated in EBMs, they can explore processes that are beyond the reach of 1D radiative-convective models (RCMs). EBMs are, however, dependent on parameterizations and tunings to account for physical processes that are neglected. Thus, EBMs rely on observations and results from GCMs and RCMs. Different EBMs have included a wide range of parameterizations (for albedo, radiation, and heat diffusion) and additional physics, such as carbon cycling and ice sheets. This CUISINES exoplanet model intercomparison project (exoMIP) will compare various EBMs across a set of numerical experiments. The set of experiments will include Earth-like planets at different obliquities, parameter sweeps across obliquity, and variations in instellation and CO 2 abundance, to produce hysteresis diagrams. We expect a range of different results due to the choices made in the various codes, highlighting which results are robust across models and which are dependent on parameterizations or other modeling choices. Additionally, the project will allow developers to identify model defects and determine which parameterizations are most useful or relevant to the problem of interest. Ultimately, this exoMIP will allow us to improve the consistency between EBMs and accelerate the process of discovering habitable exoplanets.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it