<i>JWST</i> NIRISS transmission spectroscopy of the super-Earth GJ 357b, a favourable target for atmospheric retention
Bibliographic record
Abstract
ABSTRACT We present a JWST Near Infrared Imager and Slitless Spectrograph/Single Object Slitless Spectroscopy transmission spectrum of the super-Earth GJ 357 b: the first atmospheric observation of this exoplanet. Despite missing the first $\sim$40 per cent of the transit due to using an out-of-date ephemeris, we still recover a transmission spectrum that does not display any clear signs of atmospheric features. We perform a search for Gaussian-shaped absorption features within the data but find that this analysis yields comparable fits to the observations as a flat line. We compare the transmission spectrum to a grid of atmosphere models and reject, to 3$\sigma$ confidence, atmospheres with metallicities $\lesssim 100\times$ solar ($\sim$4 g mol−1) with clouds at pressures down to 0.01 bar. We analyse how the retention of a secondary atmosphere on GJ 357 b may be possible due to its higher escape velocity compared to an Earth-sized planet and the exceptional inactivity of its host star relative to other M2.5V stars. The star’s XUV luminosity decays below the threshold for rapid atmospheric escape early enough that the volcanic revival of an atmosphere of several bars of CO$_2$ is plausible, though subject to considerable uncertainty. Finally, we model the feasibility of detecting an atmosphere on GJ 357 b with MIRI/LRS, MIRI photometry, and NIRSpec/G395H. We find that, with two eclipses, it would be possible to detect features indicative of an atmosphere or surface. Further to this, with three to four transits, it would be possible to detect a 1 bar nitrogen-rich atmosphere with 1000 ppm of CO$_2$.
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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 | 0.000 |
| 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) | 0.002 | 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".