{"id":"W2541930078","doi":"10.1109/icdsc.2013.6778241","title":"Distributed activity recognition in camera networks via low-rank matrix recovery","year":2013,"lang":"en","type":"article","venue":"","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Rank (graph theory); Activity recognition; Process (computing); Class (philosophy); Matrix (chemical analysis); Artificial intelligence; Action recognition; Computer vision; Machine learning; Pattern recognition (psychology); Data mining; Mathematics","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":[0.001111024,0.001137063,0.001485069,0.0007439516,0.0004973955,0.0009011024,0.001708187,0.001013985,0.001117717],"category_scores_gemma":[0.00346168,0.0004393321,0.000633901,0.0009612262,0.000807758,0.001930477,0.001256577,0.001589599,0.0006807265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008208362,"about_ca_system_score_gemma":0.001173148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007407287,"about_ca_topic_score_gemma":0.006768286,"domain_scores_codex":[0.9986437,0.0003575973,0.0000553428,0.0004831896,0.0002913765,0.0001687518],"domain_scores_gemma":[0.9982046,0.0006429741,0.0003113057,0.0003764715,0.0003410245,0.0001236518],"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":[0.000351367,0.0002435254,0.001852849,0.00008335791,0.00009595406,0.0001349339,0.0001272832,0.6672966,0.01126,0.006829018,0.003311953,0.3084131],"study_design_scores_gemma":[0.00001150853,0.00003278587,0.0002120541,0.00000166364,0.000003167819,0.00001837637,0.00001690739,0.9939594,0.001432274,0.004067886,0.0002391485,0.000004831144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01660499,0.0001097324,0.9818116,0.0001232254,0.00002036834,0.0000374993,0.0000654657,0.0007611117,0.0004660141],"genre_scores_gemma":[0.7361113,0.0001896793,0.259946,0.0001269443,0.0001005554,0.0001645193,0.0007012255,0.00008091587,0.002578897],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007407287,"threshold_uncertainty_score":0.01472831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111165732036352,"score_gpt":0.2271251391551173,"score_spread":0.2160134818347538,"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."}}