{"id":"W4414656585","doi":"10.1093/mnras/staf1659","title":"Testing the performance of cross-correlation techniques to search for molecular features in <i>JWST</i> NIRSpec G395H observations of transiting exoplanets","year":2025,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Space Agency; Science Mission Directorate; European Social Fund; Agencia Nacional de Investigación y Desarrollo; Agencia Estatal de Investigación; Fondation Sanofi Espoir; KU Leuven; European Commission; European Space Agency; Imperial College London; National Aeronautics and Space Administration; Deutsche Forschungsgemeinschaft; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Space Telescope Science Institute; Ministerio de Ciencia e Innovación; California Department of Fish and Game","keywords":"Exoplanet; James Webb Space Telescope; Normalization (sociology); Gaussian; Spectral line; Wavelength","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004422592,0.0008147245,0.0004168631,0.002506658,0.0006268767,0.0006650552,0.0009869726,0.001005747,0.001095501],"category_scores_gemma":[0.01132254,0.0002500136,0.0009680271,0.001494469,0.0003645357,0.001522311,0.001159532,0.0007465929,0.0004872002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000432259,"about_ca_system_score_gemma":0.0006770532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0071981,"about_ca_topic_score_gemma":0.004909851,"domain_scores_codex":[0.9984855,0.0004479081,0.0001363503,0.0003851766,0.0003303502,0.0002147359],"domain_scores_gemma":[0.9868058,0.008849546,0.001235557,0.0008275299,0.00153046,0.0007511636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003514449,0.002030669,0.5810295,0.0003058589,0.002133761,0.0004577081,0.0005802641,0.1183272,0.09729792,0.001605346,0.003800718,0.1889165],"study_design_scores_gemma":[0.00009324182,0.00133749,0.2150043,0.00001985068,0.0002256021,0.0003662087,0.0003133912,0.743225,0.03794819,0.0003485389,0.00103926,0.00007894283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9871234,0.0001176251,0.01067413,0.00008707345,0.00002601471,0.00003159021,0.0003458052,0.0005630899,0.00103131],"genre_scores_gemma":[0.9717704,0.00005172346,0.02620905,0.00006381065,0.00003008039,0.00004322786,0.001306344,0.0001455005,0.0003798051],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0071981,"threshold_uncertainty_score":0.02338916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01656040597485745,"score_gpt":0.27361151113248,"score_spread":0.2570511051576225,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}