{"id":"W1988661984","doi":"10.5539/cis.v2n1p126","title":"Tracking High Speed Skater by Using Multiple Model","year":2009,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Computer science; Tracking (education)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004481174,0.0008671465,0.001393879,0.001496461,0.0006194761,0.001135128,0.001061432,0.001352907,0.002511026],"category_scores_gemma":[0.0009085048,0.0008162627,0.001171789,0.001242568,0.0003301024,0.001168513,0.0009422469,0.0008830324,0.001850071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005906034,"about_ca_system_score_gemma":0.0005389752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009787017,"about_ca_topic_score_gemma":0.0111773,"domain_scores_codex":[0.999688,0.00004009522,0.00001013226,0.0001283602,0.00008614166,0.00004729794],"domain_scores_gemma":[0.9997392,0.00005464051,0.00003106791,0.00006076042,0.00008392058,0.00003039208],"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":[0.0008225551,0.0002657001,0.007158973,0.000122217,0.0004738864,0.0002105532,0.0001703899,0.4738591,0.03611642,0.002553338,0.004879298,0.4733675],"study_design_scores_gemma":[0.000006911128,0.00002341972,0.0009095664,0.000004103609,0.00001856395,0.00003573122,0.00001155442,0.9961622,0.001779403,0.0004894813,0.0005502012,0.000008790792],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07862379,0.0003801123,0.9125648,0.0001675265,0.0002313374,0.00006414708,0.000309699,0.002369683,0.005288948],"genre_scores_gemma":[0.7623041,0.0003642128,0.2238574,0.0001644635,0.00009521151,0.0001282268,0.0009895999,0.0002724986,0.01182438],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009787017,"threshold_uncertainty_score":0.01946014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03309069761525933,"score_gpt":0.2911654031703595,"score_spread":0.2580747055551002,"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."}}