{"id":"W1994305157","doi":"10.1109/tpami.2008.91","title":"Correction to \"Gaussian Process Dynamical Models for Human Motion\" [Feb 08 283-298]","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"Human Motion and Animation","field":"Engineering","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Gaussian process; Computer science; Artificial intelligence; Process (computing); Motion (physics); Computer vision; Gaussian; Physics; Programming language","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":[0.002777003,0.003290089,0.002237557,0.004069593,0.003245899,0.003633576,0.004971611,0.007824584,0.0911369],"category_scores_gemma":[0.03870579,0.001749622,0.002558913,0.004012985,0.002046323,0.003716302,0.002849372,0.01135003,0.048769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003521238,"about_ca_system_score_gemma":0.002885394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02283483,"about_ca_topic_score_gemma":0.02899706,"domain_scores_codex":[0.9963412,0.0005739619,0.0003720758,0.0005640079,0.001859404,0.0002893831],"domain_scores_gemma":[0.9837497,0.002618085,0.0006976192,0.001666294,0.01067395,0.0005942418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004253335,0.000006362495,0.00003785116,0.00009345054,0.00001580097,0.0001871114,0.00003405116,0.0002300408,0.0001582263,0.003208974,0.990516,0.005469613],"study_design_scores_gemma":[0.00005377754,0.00003551971,0.0006570424,0.0002470153,0.00004063738,0.0006009262,0.00007634771,0.004998867,0.000951761,0.01004612,0.9822069,0.00008503826],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0003388511,0.002032353,0.01772191,0.0351738,0.9332752,0.0000432106,0.001728534,0.00389347,0.005792663],"genre_scores_gemma":[0.03765989,0.01001891,0.04461119,0.07880452,0.3291525,0.0004532188,0.009882945,0.009323777,0.4800931],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.0911369,"threshold_uncertainty_score":0.3048833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.025949327593203,"score_gpt":0.2749729490693479,"score_spread":0.2490236214761449,"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."}}