{"id":"W2909408920","doi":"10.1109/iemcon.2018.8615054","title":"Video Predictive Object Detector","year":2018,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Artificial intelligence; Object detection; Detector; Computer vision; Feature (linguistics); Video tracking; Object (grammar); Pattern recognition (psychology); Feature extraction; Tracking (education); Layer (electronics)","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":[0.0009149958,0.001254837,0.001089719,0.001469123,0.0003696857,0.001100564,0.002143017,0.001329863,0.003444133],"category_scores_gemma":[0.002162701,0.0004642135,0.000660528,0.00121079,0.0003727242,0.001370121,0.001134565,0.001353573,0.002373118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001031025,"about_ca_system_score_gemma":0.001025972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007390932,"about_ca_topic_score_gemma":0.009226903,"domain_scores_codex":[0.9994578,0.00003864506,0.00001557389,0.000231749,0.0001599175,0.00009635901],"domain_scores_gemma":[0.9993111,0.0001892881,0.00005269445,0.0001121101,0.0002912036,0.00004376934],"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":[0.0005903231,0.0002304892,0.004759232,0.0001994079,0.0001211578,0.0003019351,0.00006326001,0.05143786,0.03360733,0.006318327,0.03857054,0.8638],"study_design_scores_gemma":[0.00002237331,0.0001154433,0.001962004,0.0000322081,0.00004473904,0.0002528708,0.00003284843,0.9532515,0.03119509,0.004551107,0.008512896,0.00002688315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03829538,0.002096465,0.9369869,0.0005366602,0.0006564077,0.0002376268,0.002436382,0.01027842,0.008475847],"genre_scores_gemma":[0.5006306,0.001324765,0.4677485,0.001069243,0.0003435342,0.0003205855,0.00794579,0.0004879891,0.020129],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007390932,"threshold_uncertainty_score":0.01469582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02042811941407555,"score_gpt":0.2903070092912015,"score_spread":0.2698788898771259,"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."}}