{"id":"W4400418492","doi":"10.1007/s40747-024-01509-w","title":"Multi-view subspace clustering based on multi-order neighbor diffusion","year":2024,"lang":"en","type":"article","venue":"Complex & Intelligent Systems","topic":"AI and Multimedia in Education","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; University of Alberta; National Science Foundation","keywords":"Computational intelligence; Cluster analysis; Order (exchange); Diffusion; Subspace topology; Computer science; Pattern recognition (psychology); Mathematics; Data mining; Artificial intelligence; Physics; Business","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004664042,0.000348783,0.0003514815,0.0003016359,0.0001981977,0.0005716066,0.0009226939,0.0001187179,0.00009307394],"category_scores_gemma":[0.0001006661,0.0002920362,0.0001532646,0.0006419618,0.00005033468,0.0002667442,0.0002119411,0.0002604875,0.00125691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002686011,"about_ca_system_score_gemma":0.0001362065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000273924,"about_ca_topic_score_gemma":0.0001180443,"domain_scores_codex":[0.9975367,0.0001952217,0.0005551621,0.0007985698,0.000445673,0.0004687239],"domain_scores_gemma":[0.9982091,0.0003529984,0.0001196344,0.0009283381,0.0001714489,0.0002185504],"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":[0.0001333065,0.006703686,0.005866184,0.009199755,0.0005313574,0.0004209656,0.04268386,0.2113114,0.05186367,0.03501426,0.06715376,0.5691178],"study_design_scores_gemma":[0.0002009805,0.00007453092,0.001015728,0.0006907249,0.000010484,0.00001271265,0.0001633263,0.9024189,0.0003352961,0.000007732478,0.09476369,0.0003058913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001543438,0.00216624,0.983806,0.0008053235,0.009657978,0.0009000746,0.000008314056,0.0006367263,0.0004758653],"genre_scores_gemma":[0.9367914,0.0001190204,0.05927566,0.0004213022,0.0005399526,0.0002172858,0.00004648486,0.00005905929,0.002529883],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9352479,"threshold_uncertainty_score":0.9999532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08264802186729615,"score_gpt":0.3291653619423766,"score_spread":0.2465173400750804,"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."}}