{"id":"W2189091799","doi":"","title":"VIVA lab - University of Ottawa at TRECVID 2009 Content Based Copy Detection","year":2009,"lang":"en","type":"article","venue":"TRECVID","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Frame (networking); Computer science; Byte; Sound quality; Artificial intelligence; Speech recognition; Computer vision; Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001623208,0.0001110632,0.0001709908,0.0000812258,0.0001683783,0.0000280307,0.0003841243,0.00006076796,0.000113198],"category_scores_gemma":[0.00001638173,0.0001107709,0.00007810218,0.0003035747,0.0000443007,0.0002677711,0.00004909682,0.00007783757,0.0000509697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008111504,"about_ca_system_score_gemma":0.00005679018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008122955,"about_ca_topic_score_gemma":0.0000944045,"domain_scores_codex":[0.9991272,0.00005686845,0.0001442222,0.0002756687,0.0001984108,0.0001976037],"domain_scores_gemma":[0.9993512,0.00004280111,0.0001416861,0.0002997769,0.00008160235,0.00008290763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001669964,0.0003390689,0.001567182,0.00005463466,0.00002954502,0.00007490128,0.001225804,0.0004115227,0.137156,0.0014996,0.01335551,0.8441193],"study_design_scores_gemma":[0.003912173,0.0008647054,0.02925605,0.0001767723,0.00005291108,0.00002860664,0.0001484176,0.05800201,0.8082725,0.0006184898,0.09797805,0.0006893073],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2458509,0.0003270847,0.7350781,0.003781423,0.0003808443,0.0002005668,0.000009537267,0.0003510219,0.01402048],"genre_scores_gemma":[0.9878272,0.000008510092,0.009664129,0.000817883,0.00003334153,2.282169e-7,0.000002177298,0.000003849965,0.001642709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8434299,"threshold_uncertainty_score":0.4517107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02460914566194398,"score_gpt":0.2079152240382909,"score_spread":0.1833060783763469,"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."}}