Unifying High- and Low-resolution Observations to Constrain the Dayside Atmosphere of KELT-20b/MASCARA-2b
Bibliographic record
Abstract
Abstract We present high-resolution dayside thermal emission observations of the exoplanet KELT-20b/MASCARA-2b using the MAROON-X spectrograph. Applying the cross-correlation method with both empirical and theoretical masks and a retrieval analysis, we confirm previous detections of Fe i emission lines and we detect Ni i for the first time in the planet (at 4.7 σ confidence). We do not see evidence for additional species in the MAROON-X data, including notably predicted thermal inversion agents TiO and VO, their atomic constituents Ti i and V i , and previously claimed species Fe ii and Cr i . We also perform a joint retrieval with existing Hubble Space Telescope/WFC3 spectroscopy and Spitzer/IRAC photometry. This allows us to place bounded constraints on the abundances of Fe i , H 2 O, and CO, and to place a stringent upper limit on the TiO abundance. The results are consistent with KELT-20b having a solar to slightly supersolar composition atmosphere in terms of the bulk metal enrichment, and the carbon-to-oxygen and iron-to-oxygen ratios. However, the TiO volume mixing ratio upper limit (10 −7.6 at 99% confidence) is inconsistent with this picture, which, along with the nondetection of Ti i , points to sequestration of Ti species, possibly due to nightside condensation. The lack of TiO but the presence of a large H 2 O emission feature in the WFC3 data is challenging to reconcile within the context of 1D self-consistent, radiative-convective models.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".