BOWIE-ALIGN: weak spectral features in KELT-7b’s <i>JWST</i> NIRSpec/G395H transmission spectrum imply a high cloud deck or a low-metallicity atmosphere
Bibliographic record
Abstract
ABSTRACT Hot Jupiters and their atmospheres are prime targets for transmission spectroscopy due to their extended atmospheres and the corresponding large signal-to-noise, providing the best possible constraints for the atmospheric carbon-to-oxygen (C/O) ratio and metallicity of exoplanets. Within BOWIE-ALIGN, we aim to compare JWST spectra of a sample of orbitally aligned and misaligned hot Jupiters orbiting F-type stars to probe the link between hot Jupiter atmospheres and planet formation history. Here, we present a near-infrared transmission spectrum of the aligned planet KELT-7b using one transit observed with JWST NIRSpec/G395H. We find weak features, only tentative evidence for H$_2$O and CO$_2$ in the atmosphere of KELT-7b. This poses a challenge to constrain the atmospheric properties of KELT-7b and two possible scenarios emerge from equilibrium chemistry and free chemistry retrievals: a high-altitude cloud deck muting all features or an extremely low metallicity atmosphere, respectively. The retrieved C/O ratios from our data reductions range from $0.43{\!-\!}0.74$, while the atmospheric metallicity is suggested to be solar to super-solar ($1{\!-\!}16 \times$ solar). Although these wide constraints prevent detailed conclusions about KELT-7b’s formation history, a solar-to-super-solar metallicity would imply the accretion of solid material during its formation, which is valuable information for the survey’s wider goals of understanding the relative importance of gaseous to solid accretion.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".