{"id":"W4293223831","doi":"10.11159/mhci22.109","title":"Video Analysis Tool with Template Matching and Audio-Track Processing","year":2022,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"Universidad del Atlántico","keywords":"Computer science; Track (disk drive); Matching (statistics); Audio signal processing; Computer vision; Artificial intelligence; Speech recognition; Computer graphics (images); Speech coding; Audio signal","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0008433476,0.001531966,0.0009089446,0.004739679,0.0006126013,0.00159545,0.002618134,0.00154693,0.02992788],"category_scores_gemma":[0.00349065,0.000543962,0.001279066,0.002145193,0.0003586055,0.00155709,0.001231365,0.0007497051,0.01347113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005390569,"about_ca_system_score_gemma":0.0008060936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003078005,"about_ca_topic_score_gemma":0.002603437,"domain_scores_codex":[0.9989298,0.00007044816,0.0001088738,0.0003520413,0.0004451127,0.00009370178],"domain_scores_gemma":[0.9988909,0.0003083256,0.00009999439,0.0002073632,0.0004235897,0.00006982478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004759032,0.0002426613,0.00123171,0.0004031555,0.000132758,0.0004619479,0.0002295506,0.005176047,0.0718617,0.003393625,0.03705607,0.8793349],"study_design_scores_gemma":[0.0002160101,0.000448143,0.006103574,0.0001290876,0.0001715272,0.002200274,0.0003638639,0.4987775,0.3344506,0.008429341,0.1484426,0.0002674239],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00326882,0.00009548352,0.9351937,0.00005921558,0.00009691394,0.0002797222,0.0009915874,0.05733269,0.002681974],"genre_scores_gemma":[0.03971411,0.0001417847,0.944823,0.0001276845,0.0000883815,0.0006396726,0.003340127,0.003534738,0.00759059],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02992788,"threshold_uncertainty_score":0.1001188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004623011767010912,"score_gpt":0.1901666372531261,"score_spread":0.1855436254861152,"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."}}