{"id":"W4394967016","doi":"10.1109/tii.2024.3383534","title":"Nonlinear Slow Feature Analysis for Oscillating Characteristics Under Deep Encoder-Decoder Framework","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Informatics","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Nonlinear system; Encoder; Feature (linguistics); Control theory (sociology); Artificial intelligence; Pattern recognition (psychology); Electronic engineering; Physics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001690745,0.0002328936,0.0002763581,0.0003664474,0.0002455542,0.0003616409,0.0001696515,0.0004534875,0.00005297527],"category_scores_gemma":[0.00001546593,0.0002257447,0.0002381682,0.001111861,0.00003693045,0.0003111519,0.000001532637,0.0008462683,0.00002897212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001238373,"about_ca_system_score_gemma":0.00005739043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002897462,"about_ca_topic_score_gemma":0.000004381302,"domain_scores_codex":[0.9988856,0.000007940044,0.0005151676,0.0001260628,0.0001821446,0.0002830464],"domain_scores_gemma":[0.9992285,0.0002585431,0.00006087648,0.0002821466,0.00008400319,0.00008592472],"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":[0.00002857265,0.00008552053,0.000009119325,0.000454615,0.001304118,0.000001427903,0.002023164,0.7657322,0.0002195994,0.0007798334,0.003694368,0.2256675],"study_design_scores_gemma":[0.0001391117,0.00003604089,0.000002128795,0.0001312924,0.0005054803,0.000003591721,0.0001952695,0.9809091,0.004485348,0.0004860579,0.01283492,0.0002716412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002270486,0.00003577086,0.9944952,0.0002656893,0.0008164993,0.0003727421,0.0003590611,0.001031072,0.0003534929],"genre_scores_gemma":[0.7158421,0.00009059178,0.2826095,0.0002025515,0.0005055279,0.0002404807,0.00009757903,0.00007486544,0.0003367322],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7135717,"threshold_uncertainty_score":0.9205601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03431548053878632,"score_gpt":0.2831658299236005,"score_spread":0.2488503493848141,"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."}}