{"id":"W4288079846","doi":"10.1051/swsc/2020051","title":"Towards an algebraic method of solar cycle prediction","year":2020,"lang":"en","type":"article","venue":"Journal of Space Weather and Space Climate","topic":"Solar and Space Plasma Dynamics","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Collège de Bois-de-Boulogne","funders":"Nemzeti Kutatási, Fejlesztési és Innovaciós Alap; Science and Technology Facilities Council; H2020 Research Infrastructures; Nemzeti Kutatási Fejlesztési és Innovációs Hivatal; European Commission","keywords":"Dynamo; Dipole; Moment (physics); Sunspot; Physics; Solar cycle; Set (abstract data type); Fraction (chemistry); Amplitude; Ranking (information retrieval); Statistical physics; Algebraic number; Mathematics; Computer science; Solar wind; Mathematical analysis; Classical mechanics; Quantum mechanics; Artificial intelligence; Chemistry; Magnetic field","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004416358,0.0001801344,0.0004288872,0.00007405167,0.00008190742,0.00005948488,0.0001440676,0.00006632854,0.0001224654],"category_scores_gemma":[0.00001718379,0.0001484685,0.0001831342,0.0001487112,0.00004823279,0.0003713539,0.00005382112,0.0003015781,0.000004403483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001289174,"about_ca_system_score_gemma":0.00005703203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005211306,"about_ca_topic_score_gemma":0.000004440648,"domain_scores_codex":[0.9989138,0.00009207369,0.0003445307,0.0001687372,0.0002409223,0.0002399537],"domain_scores_gemma":[0.9990225,0.00004726135,0.0003888135,0.0001349145,0.0001360164,0.0002705144],"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":[0.001425991,0.001030331,0.7345623,0.0003855782,0.00131293,0.0000510223,0.02728085,0.007848341,0.1204339,0.06231524,0.001595387,0.04175816],"study_design_scores_gemma":[0.01690645,0.009847958,0.2227034,0.0008301687,0.002617307,0.00029972,0.08833347,0.5293756,0.07522086,0.0325965,0.01869524,0.002573383],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8888814,0.0001903792,0.1038696,0.002941065,0.0001531894,0.0001188002,0.0001068611,0.00002023478,0.003718405],"genre_scores_gemma":[0.9810823,0.000118504,0.01836295,0.00006494861,0.0002880825,0.000001202726,0.000005466116,0.00003003797,0.00004652841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5215272,"threshold_uncertainty_score":0.6054369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01019395239374093,"score_gpt":0.2601650683188148,"score_spread":0.2499711159250738,"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."}}