{"id":"W4381948276","doi":"10.26464/epp2023055","title":"Ground-based and additional science support for SMILE","year":2023,"lang":"en","type":"article","venue":"Earth and Planetary Physics","topic":"Ionosphere and magnetosphere dynamics","field":"Physics and Astronomy","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Science and Technology Facilities Council; Canadian Space Agency; Natural Environment Research Council; National Natural Science Foundation of China; Deutsche Forschungsgemeinschaft; Sight Research UK; UK Space Agency; Norges Forskningsråd; National Science Foundation; European Space Agency; National Aeronautics and Space Administration; Swedish National Space Agency","keywords":"Spacecraft; Context (archaeology); Space Science; Solar wind; Scale (ratio); Interplanetary spaceflight; Ionosphere; Space weather; Space (punctuation); Radar; Computer science; Geophysics; Meteorology; Physics; Geography; Astronomy; Telecommunications; Magnetic field","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":[0.01055307,0.0005613741,0.0005595475,0.001856345,0.002389284,0.002009355,0.001439948,0.001520621,0.03310323],"category_scores_gemma":[0.01492994,0.0001725304,0.0005632208,0.001829363,0.0009233843,0.002857869,0.006143557,0.00201797,0.009111932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009292371,"about_ca_system_score_gemma":0.004710677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002758913,"about_ca_topic_score_gemma":0.004889939,"domain_scores_codex":[0.9960717,0.0009200869,0.00009426056,0.0003106569,0.001697037,0.0009062237],"domain_scores_gemma":[0.971688,0.004011191,0.001287003,0.009279811,0.008523139,0.005210861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002296909,0.000710881,0.03149185,0.0006960004,0.000156961,0.0007246002,0.002036206,0.001990467,0.06393786,0.02543977,0.4536397,0.4168788],"study_design_scores_gemma":[0.0003270922,0.001100345,0.03744478,0.0001656118,0.00005955701,0.0003893451,0.001727586,0.004193196,0.01347067,0.008380874,0.9326682,0.00007269628],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2193165,0.002113599,0.06704049,0.05416407,0.005872191,0.001643229,0.02998451,0.009866399,0.6099991],"genre_scores_gemma":[0.7810476,0.00132604,0.06619902,0.01424575,0.002723557,0.001405003,0.04845931,0.002112113,0.08248147],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03310323,"threshold_uncertainty_score":0.1107413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008738197488042793,"score_gpt":0.20588986830091,"score_spread":0.1971516708128672,"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."}}