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Record W4415961990 · doi:10.3847/1538-3881/ae019a

A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum

2025· article· en· W4415961990 on OpenAlexfundno aff
Stephen P. Schmidt, Ryan J. MacDonald, Shang‐Min Tsai, Michael Radica, Le Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel Thorngren, Nicholas F. Wogan, Erin May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López‐Morales, David K. Sing

Bibliographic record

VenueThe Astronomical Journal · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaSpace Telescope Science InstituteNuclear Safety and Security CommissionCalifornia Institute of TechnologyNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsRobustness (evolution)Atmospheric compositionSpectral lineData reductionHydrogen moleculeAtmospheric modelRange (aeronautics)Polarization (electrochemistry)

Abstract

fetched live from OpenAlex

Abstract Sub-Neptunes are the most common type of planet in our galaxy. Interior structure models suggest that the coldest sub-Neptunes could host liquid water oceans underneath their hydrogen envelopes—sometimes called “hycean” planets. JWST transmission spectra of the ∼250 K sub-Neptune K2-18 b were recently used to report detections of CH 4 and CO 2 , alongside weaker evidence of (CH 3 ) 2 S (dimethyl sulfide, or DMS). Atmospheric CO 2 was interpreted as evidence for a liquid water ocean, while DMS was highlighted as a potential biomarker. However, these notable claims were derived using a single data reduction and retrieval modeling framework, which did not allow for standard robustness tests. Here, we present a comprehensive reanalysis of K2-18 b’s JWST NIRISS SOSS and NIRSpec G395H transmission spectra, including the first analysis of the second-order NIRISS SOSS data. We incorporate multiple well-tested data reduction pipelines and retrieval codes, spanning 60 different data treatments and over 250 atmospheric retrievals. We confirm the detection of CH 4 (≈4 σ ), with a volume mixing ratio range <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo>−</mml:mo> <mml:mn>2.14</mml:mn> <mml:mo>≤</mml:mo> <mml:msub> <mml:mrow> <mml:mi>log</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> </mml:msub> <mml:msub> <mml:mrow> <mml:mi mathvariant="normal">CH</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> <mml:mo>≤</mml:mo> <mml:mo>−</mml:mo> <mml:mn>0.53</mml:mn> </mml:math> , but we find no statistically significant or reliable evidence for CO 2 or DMS. Finally, we assess the retrieved atmospheric composition using photochemical-climate and interior models, demonstrating that our revised composition of K2-18 b can be explained by an oxygen-poor mini-Neptune without requiring a liquid water surface or life.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.249
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2025
Admission routes1
Has abstractyes

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