{"id":"W2082340226","doi":"10.1186/bf03351929","title":"Multi-step prediction of Dst index using singular spectrum analysis and locally linear neurofuzzy modeling","year":2006,"lang":"en","type":"article","venue":"Earth Planets and Space","topic":"Statistical and numerical algorithms","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Singular spectrum analysis; Index (typography); Time series; Series (stratigraphy); Computer science; Set (abstract data type); Geomagnetic storm; Data mining; Linear prediction; Mathematics; Algorithm; Earth's magnetic field; Machine learning; Geology; Singular value decomposition","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004513298,0.0003433918,0.0003312884,0.0004722612,0.0001611441,0.0003114702,0.0002957983,0.0002841468,0.0004937368],"category_scores_gemma":[0.00135529,0.0001256145,0.0003186314,0.0002919607,0.0002392619,0.0003610589,0.0001954565,0.000368463,0.00009961445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003948209,"about_ca_system_score_gemma":0.0003941454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009618915,"about_ca_topic_score_gemma":0.007665139,"domain_scores_codex":[0.9998821,0.0000320227,0.000007519574,0.00003109963,0.00003760214,0.000009737866],"domain_scores_gemma":[0.9995735,0.000229946,0.00006206326,0.0000256007,0.00008680999,0.00002200901],"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":[0.00008211847,0.00005542103,0.003758724,0.00002647089,0.000045786,0.00007511277,0.00004912772,0.9162482,0.00824711,0.001139319,0.0003024424,0.06997017],"study_design_scores_gemma":[7.004638e-7,0.000003578044,0.0002089719,4.986102e-7,0.000001144462,0.00000164996,0.000001023473,0.999326,0.000271547,0.0001730614,0.00001077479,0.000001035789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2736697,0.000134374,0.724655,0.0001304333,0.00002564198,0.00002184853,0.0000541133,0.0004165283,0.0008924085],"genre_scores_gemma":[0.9663503,0.00002848071,0.03316189,0.0000101773,0.000009357967,0.00001420549,0.00003118796,0.000009303208,0.0003850636],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009618915,"threshold_uncertainty_score":0.01912582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03189091552789861,"score_gpt":0.2629936502531301,"score_spread":0.2311027347252315,"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."}}