{"id":"W4406262159","doi":"10.1109/qce60285.2024.00190","title":"QuaCK-TSF: Quantum-Classical Kernelized Time Series Forecasting","year":2024,"lang":"en","type":"article","venue":"","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thales (Canada); Polytechnique Montréal; Institut quantique; Université de Sherbrooke","funders":"","keywords":"Computer science; Series (stratigraphy); Artificial intelligence; Time series; Machine learning; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001776873,0.0006114883,0.001030564,0.0006421452,0.000565491,0.001442711,0.001907214,0.001432773,0.004062357],"category_scores_gemma":[0.008004956,0.0003427256,0.0005702635,0.001039754,0.0008645208,0.002949503,0.001509155,0.001790359,0.0009579988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001101878,"about_ca_system_score_gemma":0.001624067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009506138,"about_ca_topic_score_gemma":0.006238448,"domain_scores_codex":[0.9993827,0.0001894445,0.0000421825,0.00009256115,0.0002275909,0.00006556736],"domain_scores_gemma":[0.9978528,0.001051778,0.0001649026,0.0004003144,0.0004133559,0.0001168594],"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":[0.0001202668,0.00008428516,0.0008026012,0.00008505103,0.00006615366,0.0000909305,0.00006732307,0.7548994,0.001788616,0.1332805,0.005243816,0.1034711],"study_design_scores_gemma":[0.000002318074,0.000004762107,0.00003793859,0.000002001599,0.00000161728,0.000005408092,0.000002004394,0.9869573,0.0002219515,0.01233661,0.0004234549,0.000004630323],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01172184,0.0002927612,0.9835429,0.0004561101,0.0001204308,0.00003050626,0.0001336278,0.0009603967,0.002741383],"genre_scores_gemma":[0.6850641,0.0006438438,0.3066411,0.0003039905,0.0002111579,0.0001118746,0.0005491255,0.0003987273,0.006075964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009506138,"threshold_uncertainty_score":0.01890159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04348239819781969,"score_gpt":0.2169379482157828,"score_spread":0.1734555500179631,"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."}}