Ground- and Space-based Detection of the Thermal Emission Spectrum of the Transiting Hot Jupiter KELT-2Ab
Bibliographic record
Abstract
Abstract We describe the detection of water vapor in the atmosphere of the transiting hot Jupiter KELT-2Ab by treating the star–planet system as a spectroscopic binary with high-resolution, ground-based spectroscopy. We resolve the signal of the planet’s motion with deep combined flux observations of the star and the planet. In total, six epochs of Keck NIRSPEC L -band observations were obtained, and the full data set was subjected to a cross-correlation analysis with a grid of self-consistent atmospheric models. We measure a radial projection of the Keplerian velocity, K P , of 148 ± 7 km s −1 , consistent with transit measurements, and detect water vapor at 3.8 σ . We combine NIRSPEC L -band data with Spitzer IRAC secondary eclipse data to further probe the metallicity and carbon-to-oxygen ratio of KELT-2Ab’s atmosphere. While the NIRSPEC analysis provides few extra constraints on the Spitzer data, it does provide roughly the same constraints on metallicity and carbon-to-oxygen ratio. This bodes well for future investigations of the atmospheres of non-transiting hot Jupiters.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".