{"id":"W3174863573","doi":"10.5121/csit.2021.110807","title":"Data-Driven Intelligent Application for Youtube Video Popularity Analysis using Machine Learning and Statistics","year":2021,"lang":"en","type":"article","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Popularity; Computer science; Pace; Process (computing); Web page; Online video; Support vector machine; World Wide Web; Multimedia; Artificial intelligence","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":[0.0003417062,0.00008468003,0.0002045929,0.0001189861,0.0001939019,0.0002299465,0.000285239,0.00003620539,0.00001828021],"category_scores_gemma":[0.0001635439,0.00007901844,0.00004949289,0.0008001079,0.00001275588,0.0003030522,0.0004020366,0.00006563588,0.000001558268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002688025,"about_ca_system_score_gemma":0.00004022319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000459749,"about_ca_topic_score_gemma":0.002185771,"domain_scores_codex":[0.9988974,0.00007677427,0.0002619097,0.0004781082,0.0001631853,0.0001226381],"domain_scores_gemma":[0.9990267,0.00008207476,0.00009969712,0.0005202536,0.0002117334,0.00005952708],"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":[0.000009968571,0.0002029484,0.315291,0.00008238928,0.001581779,0.000009710614,0.0005053346,0.08700731,0.004191882,0.2508388,0.0001730576,0.3401058],"study_design_scores_gemma":[0.00006708863,0.000009101742,0.001130457,0.000001792091,0.0003771448,0.000001429579,0.00003629073,0.9937191,0.0003159633,0.001268974,0.00297425,0.00009839297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001717073,0.0001542818,0.9976954,0.0001410233,0.00002798057,0.0001040313,0.00009218951,0.00003873594,0.00002931784],"genre_scores_gemma":[0.2449225,0.00008968316,0.7524839,0.0001100857,0.00002610641,0.00000725497,0.002159215,0.000005875702,0.0001953078],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9067118,"threshold_uncertainty_score":0.3222279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05047002889684182,"score_gpt":0.3237213830961041,"score_spread":0.2732513541992623,"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."}}