Are there Spectral Features in the MIRI/LRS Transmission Spectrum of K2-18b?
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Bibliographic record
Abstract
Determining the composition of an exoplanet atmosphere relies on the presence of detectable spectral features. The strongest spectral features, including DMS, look approximately Gaussian. Here, I perform a suite of Gaussian feature analyses to find any statistically significant spectral features in the recently published MIRI/LRS spectrum of K2-18b (N. Madhusudhan et al. 2025). In N. Madhusudhan et al. 2025, they claim a 3.4-$σ$ detection of spectral features compared to a flat line. In 5 out of 6 tests, I find the data preferred a flat line over a Gaussian model, with a $χ^{2}_ν$ of 1.06. When centering the Gaussian where the absorptions for DMS and DMDS peak, I find ln(B) = 1.21 in favour of the Gaussian model, with a $χ^{2}_ν$ of 0.99. With only $\sim$2-$σ$ in favour of Gaussian features, I conclude no strong statistical evidence for spectral features.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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