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Record W4319604418 · doi:10.1088/1538-3873/aca3d3

Spectroscopic Time-series Performance of JWST/NIRSpec from Commissioning Observations

2023· article· en· W4319604418 on OpenAlexaff
Néstor Espinoza, Leonardo Úbeda, Stephan M. Birkmann, Pierre Ferruit, Jeff A. Valenti, David K. Sing, Zafar Rustamkulov, Michael Regan, Sarah Kendrew, Elena Sabbi, Everett Schlawin, Thomas G. Beatty, Loïc Albert, Thomas P. Greene, Nikolay Nikolov, Diane Karakla, Charles Keyes, Catarina Alves de Oliveira, Torsten Böker, María Peña-Guerrero, Giovanna Giardino, Nimisha Kumari, Elena Manjavacas, Charles Proffitt, Tim Rawle

Bibliographic record

VenuePublications of the Astronomical Society of the Pacific · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsExoplanetTransit (satellite)Series (stratigraphy)PhysicsFilter (signal processing)James Webb Space TelescopeAstronomyAstrophysicsPlanetComputer scienceTelescopeEngineeringBiology

Abstract

fetched live from OpenAlex

Abstract We report on James Webb Space Telescope (JWST) commissioning observations of the transiting exoplanet HAT-P-14 b, obtained using the Bright Object Time Series (BOTS) mode of the NIRSpec instrument with the G395H/F290LP grating/filter combination (3–5 μ m). While the data were used primarily to verify that the NIRSpec BOTS mode is working as expected, and to enable it for general scientific use, they yield a precise transmission spectrum which we find is featureless down to the precision level of the instrument, consistent with expectations given HAT-P-14 b’s small scale-height and hence expected atmospheric features. The exquisite quality and stability of the JWST/NIRSpec transit spectrum—almost devoid of any systematic effects—allowed us to obtain median uncertainties of 50–60 ppm in this wavelength range at a resolution of R = 100 in a single exposure, which is in excellent agreement with pre-flight expectations and close to the (or at the) photon-noise limit for a J = 9.094, F-type star like HAT-P-14. These observations showcase the ability of NIRSpec/BOTS to perform cutting-edge transiting exoplanet atmospheric science, setting the stage for observations and discoveries to be made in Cycle 1 and beyond.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.302

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.219
Teacher spread0.200 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations43
Published2023
Admission routes1
Has abstractyes

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