{"id":"W2058234427","doi":"10.1145/2661714.2661729","title":"Automatic Video Intro and Outro Detection on Internet Television","year":2014,"lang":"en","type":"article","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Histogram; Bandwidth (computing); Reliability (semiconductor); Multimedia; Key (lock); The Internet; Real-time computing; Computer network; Artificial intelligence; World Wide Web; Power (physics); Image (mathematics); Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003044096,0.00007336772,0.0001062847,0.0001167178,0.00005133791,0.0001887224,0.0001701394,0.00003455815,0.00003351337],"category_scores_gemma":[0.0001073504,0.00005424301,0.00003114539,0.0001697893,0.00001086446,0.0002541915,0.00008610503,0.00005176706,0.00007412925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001794594,"about_ca_system_score_gemma":0.000003664933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003504884,"about_ca_topic_score_gemma":0.00004404971,"domain_scores_codex":[0.9992926,0.00007259585,0.0001543502,0.0002381209,0.0001467032,0.00009565962],"domain_scores_gemma":[0.9995378,0.00007745329,0.00004998865,0.0002564249,0.00003060098,0.00004778318],"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":[0.000001511797,0.0000153093,0.0005082954,0.000005513564,0.000006695359,2.660385e-7,0.00009135449,0.00004863896,0.0007360285,0.01981062,0.0003437176,0.9784321],"study_design_scores_gemma":[0.0001260205,0.000149654,0.005536054,0.00001286921,0.000005116919,0.000001942944,0.000004719682,0.9846739,0.005486443,0.001959257,0.001971339,0.00007267752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09834266,0.000005249885,0.8989568,0.0004360199,0.0001030512,0.00004409061,4.173947e-8,0.0001271463,0.001984964],"genre_scores_gemma":[0.9930499,0.000003848625,0.006025411,0.0005162805,0.0000390383,0.000001987112,8.80951e-7,0.000003374089,0.0003592308],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9846253,"threshold_uncertainty_score":0.2211966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005523855563204349,"score_gpt":0.204811928814472,"score_spread":0.1992880732512677,"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."}}