{"id":"W3016118468","doi":"10.1093/mnras/staa981","title":"Molecular cross-sections for high-resolution spectroscopy of super-Earths, warm Neptunes, and hot Jupiters","year":2020,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Spectroscopy and Laser Applications","field":"Chemistry","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 European Research Council; European Commission; Science and Technology Facilities Council; Engineering and Physical Sciences Research Council; Institut sur la Nutrition et les Aliments Fonctionnels; European Southern Observatory","keywords":"Physics; Hot Jupiter; Astrobiology; Spectroscopy; Astronomy; High resolution; Astrophysics; Molecular spectroscopy; Planet; Exoplanet; Remote sensing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007282579,0.0001601532,0.0002528914,0.000006227416,0.0001735929,0.00003411073,0.0003028781,0.0001179027,0.00007903425],"category_scores_gemma":[0.00003944463,0.0001383506,0.0003322789,0.00007534049,0.0003299482,0.00006003964,0.0001288416,0.0001958262,0.000001700271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005942256,"about_ca_system_score_gemma":0.00003940152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003322534,"about_ca_topic_score_gemma":0.00001467308,"domain_scores_codex":[0.9989728,0.00001472594,0.0003238618,0.0003119254,0.0001289939,0.0002476349],"domain_scores_gemma":[0.9992922,0.00009672785,0.0001748447,0.0002701996,0.00005775211,0.000108267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002997968,0.0002153104,0.02467817,0.0002313552,0.0002581404,5.042817e-8,0.0007309049,0.7439375,0.2276674,0.0007232577,0.001194396,0.00006377699],"study_design_scores_gemma":[0.0008989695,0.00009778193,0.02319315,0.00001800265,0.0001479477,1.330007e-8,0.0003499196,0.2855492,0.6887909,0.00006583882,0.0007289616,0.0001593114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964696,0.0001554461,0.001321563,0.001264754,0.00004839429,0.0002067252,0.0003456957,0.00003463393,0.0001532014],"genre_scores_gemma":[0.992493,5.326175e-7,0.00713336,0.00008683443,0.0001339846,0.00004527947,0.00004210459,0.00002042412,0.00004450454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4611236,"threshold_uncertainty_score":0.5641774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00893307270381857,"score_gpt":0.2296183275198105,"score_spread":0.2206852548159919,"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."}}