{"id":"W3210472501","doi":"10.48550/arxiv.2110.11837","title":"Physically-motivated basis functions for temperature maps of exoplanets","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Stellar, planetary, and galactic studies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Hans-Sigrist-Stiftung; National Aeronautics and Space Administration; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Exoplanet; Maxima and minima; Basis function; Longitude; Physics; Hot Jupiter; Albedo (alchemy); Spherical harmonics; Computational physics; Planet; Astrophysics; Latitude; Mathematical analysis; Mathematics","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":[0.0006148776,0.000400519,0.0003194429,0.0007253768,0.0004009129,0.000919219,0.000922052,0.0005160078,0.001602653],"category_scores_gemma":[0.001864762,0.0002926024,0.0006879623,0.0005796341,0.0006304465,0.001232385,0.0005511222,0.001070687,0.0004400767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006240871,"about_ca_system_score_gemma":0.0005802084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002319452,"about_ca_topic_score_gemma":0.001710626,"domain_scores_codex":[0.9998658,0.00004529618,0.000007555803,0.00002711107,0.00003183959,0.00002251903],"domain_scores_gemma":[0.9996004,0.00009978219,0.00004846407,0.00012995,0.00008549511,0.00003604946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000471384,0.00005384669,0.002463427,0.00006101449,0.00002817534,0.00006839251,0.0001807341,0.5407354,0.0159788,0.4056117,0.002075222,0.03269621],"study_design_scores_gemma":[0.000006339698,0.000007542196,0.000738628,0.000008223519,0.000002659423,0.0000182433,0.00002316775,0.9318244,0.0009944797,0.06435768,0.002003229,0.00001540052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08500167,0.0001592727,0.910727,0.0001531211,0.0000383202,0.00003095473,0.0003724191,0.0002474932,0.003269828],"genre_scores_gemma":[0.6512702,0.0004558385,0.3432932,0.0001223086,0.00008356277,0.0002547171,0.0009560053,0.0005543444,0.003009956],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002319452,"threshold_uncertainty_score":0.005361378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03512880414145856,"score_gpt":0.1745644226866798,"score_spread":0.1394356185452212,"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."}}