{"id":"W4323051991","doi":"10.1111/sjos.12702","title":"Nonparametric plug‐in classifier for multiclass classification of S.D.E. paths","year":2024,"lang":"en","type":"article","venue":"Scandinavian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Mathematics; Nonparametric statistics; Multiclass classification; Estimator; Classifier (UML); Homogeneous; Artificial intelligence; Applied mathematics; Pattern recognition (psychology); Statistics; Algorithm; Computer science; Support vector machine; Combinatorics","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":[0.008075406,0.0008322531,0.001949489,0.002309415,0.0006719688,0.001594773,0.001905337,0.002319636,0.002129808],"category_scores_gemma":[0.02031145,0.0004300495,0.0007901497,0.001286642,0.001478757,0.001945021,0.001964649,0.002298201,0.0006310525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001146297,"about_ca_system_score_gemma":0.0008646399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001575652,"about_ca_topic_score_gemma":0.001326862,"domain_scores_codex":[0.9984547,0.0007078614,0.0000868845,0.0002798254,0.0003345311,0.0001361078],"domain_scores_gemma":[0.9855545,0.01048374,0.001020929,0.001141757,0.001413408,0.0003856324],"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":[0.0009406283,0.0006256484,0.01599481,0.0002908478,0.0001636934,0.0004728406,0.0002330784,0.4931955,0.005048166,0.06026002,0.007304585,0.4154702],"study_design_scores_gemma":[0.000009317534,0.00003616441,0.0004995674,0.000008649247,0.00000690483,0.00004195993,0.000009172878,0.9883958,0.0005154113,0.01004238,0.0004281198,0.00000660302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0852884,0.0005560202,0.9117054,0.0005264093,0.0001179382,0.00009485977,0.0001876716,0.0006879789,0.0008352597],"genre_scores_gemma":[0.8028038,0.0003422231,0.1896809,0.0002549663,0.0001943164,0.0002888667,0.0009402841,0.0001146983,0.005380073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008075406,"threshold_uncertainty_score":0.04270732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.139083926483809,"score_gpt":0.4056716622075561,"score_spread":0.2665877357237472,"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."}}