{"id":"W212225820","doi":"10.1049/iet-ipr.2011.0269","title":"Classification of surveillance video objects using chaotic series","year":2012,"lang":"en","type":"article","venue":"IET Image Processing","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Université de Montréal","funders":"","keywords":"Chaotic; Series (stratigraphy); Computer science; Feature (linguistics); Artificial intelligence; Pattern recognition (psychology); Feature vector; Support vector machine; Binary number; Computer vision; 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":[0.000368668,0.000354433,0.000438856,0.00101547,0.0002462894,0.0005615028,0.0004637846,0.0003744467,0.0003389526],"category_scores_gemma":[0.001130822,0.0001571929,0.0005769482,0.0004556967,0.0003945179,0.0005182437,0.0002956181,0.0003401529,0.0001284823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007390322,"about_ca_system_score_gemma":0.0003187687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003263062,"about_ca_topic_score_gemma":0.001981739,"domain_scores_codex":[0.9997781,0.00003910649,0.00001858931,0.0000527065,0.00008405801,0.00002752288],"domain_scores_gemma":[0.9996789,0.00009675846,0.00006958599,0.00003696822,0.00009654453,0.0000213481],"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":[0.000269232,0.0002081659,0.01031319,0.0000935766,0.0001305727,0.0002338162,0.0001613681,0.6042654,0.05991856,0.02145058,0.001267607,0.3016879],"study_design_scores_gemma":[0.000002445552,0.00003650414,0.0008223385,0.000002814854,0.000007372973,0.0000315058,0.000009028345,0.9936776,0.003778133,0.001369002,0.0002574124,0.000005955415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.134447,0.0001470968,0.8635897,0.000123797,0.00003314373,0.00006432419,0.00006799304,0.0003682089,0.001158777],"genre_scores_gemma":[0.8503196,0.0001930406,0.147731,0.00004272805,0.00004843966,0.0000585367,0.0002453767,0.00002370914,0.001337595],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003263062,"threshold_uncertainty_score":0.006488144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03148868782002451,"score_gpt":0.2839963297098604,"score_spread":0.2525076418898359,"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."}}