{"id":"W4382052193","doi":"10.1109/scm58628.2023.10159109","title":"Analysis of Artificial Intelligence Methods and Algorithms for Processing Data as a Series of Signals","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Research in Systems and Signal Processing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Science and Higher Education of the Russian Federation","keywords":"Computer science; Artificial intelligence; AdaBoost; Support vector machine; Pattern recognition (psychology); Task (project management); Field (mathematics); Machine learning; Object (grammar); Time series; Selection (genetic algorithm); Series (stratigraphy); Data mining; Algorithm; Mathematics; Engineering","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":[0.004471692,0.001402476,0.001137033,0.003932281,0.0004227069,0.003156379,0.000990724,0.0009552881,0.001790478],"category_scores_gemma":[0.01170796,0.0003646737,0.001309114,0.003198697,0.001248791,0.00242917,0.0007914403,0.001488147,0.0007750641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009391024,"about_ca_system_score_gemma":0.001400018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001122015,"about_ca_topic_score_gemma":0.0006197453,"domain_scores_codex":[0.9952263,0.0012739,0.0004243859,0.0005326998,0.002435111,0.000107609],"domain_scores_gemma":[0.9922849,0.005245968,0.0006217337,0.0006226843,0.001169894,0.00005487552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009885673,0.0001919913,0.00950911,0.003155225,0.001028257,0.0003363933,0.0002816405,0.07500169,0.007707802,0.1255634,0.00752283,0.7696028],"study_design_scores_gemma":[0.00005094462,0.0005301564,0.01603265,0.001593715,0.0004927141,0.001343878,0.0004157315,0.591822,0.01577021,0.2767739,0.09499613,0.0001779362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01085568,0.02095108,0.9548213,0.001359041,0.0004573315,0.0002396012,0.0003113706,0.0007359515,0.01026857],"genre_scores_gemma":[0.1847485,0.0293062,0.7767637,0.0009049871,0.001053338,0.00081192,0.0008846616,0.000235974,0.005290787],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004471692,"threshold_uncertainty_score":0.02364886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1992969466100113,"score_gpt":0.4664852847707862,"score_spread":0.2671883381607749,"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."}}