{"id":"W3142661537","doi":"10.1109/cbmi.2010.5529908","title":"Crim's content-based audio copy detection system for TRECVID 2009","year":2010,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Computer Research Institute of Montréal","funders":"","keywords":"Computer science; Robustness (evolution); Fingerprint (computing); k-nearest neighbors algorithm; Frame (networking); Pattern recognition (psychology); Artificial intelligence; Task (project management); Graphics; Nearest neighbor search; Speech recognition","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":[0.002781445,0.001872303,0.001501341,0.00549606,0.001093229,0.001202692,0.002200311,0.001470164,0.01151748],"category_scores_gemma":[0.008771092,0.0005686778,0.001080611,0.003361979,0.0004264633,0.001788847,0.001225043,0.0009019055,0.008296646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001630914,"about_ca_system_score_gemma":0.001127532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02928453,"about_ca_topic_score_gemma":0.03700523,"domain_scores_codex":[0.9965807,0.0004398537,0.0002111544,0.0008352837,0.001614736,0.0003183135],"domain_scores_gemma":[0.9961372,0.000768248,0.000255622,0.00116828,0.001452096,0.0002185027],"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":[0.001903137,0.0005815719,0.007350132,0.001000911,0.0007130593,0.0004978815,0.0001596132,0.006661403,0.08381822,0.001109425,0.3597479,0.5364567],"study_design_scores_gemma":[0.0009572189,0.002176902,0.07814723,0.0001458722,0.0008670316,0.004443974,0.000340052,0.4210662,0.3214731,0.002847813,0.1670495,0.0004852025],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.271922,0.004874153,0.1904506,0.0009821937,0.001393104,0.003468463,0.1007701,0.38319,0.0429494],"genre_scores_gemma":[0.3966703,0.0008732475,0.3741264,0.0003787414,0.0003881945,0.001501467,0.2000245,0.006108975,0.01992816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02928453,"threshold_uncertainty_score":0.05822814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03245280463237677,"score_gpt":0.2434685395092916,"score_spread":0.2110157348769148,"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."}}