{"id":"W2517270245","doi":"10.1109/bigmm.2016.39","title":"An Empirical Study of the Textual Content of Online Videos","year":2016,"lang":"en","type":"article","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Information retrieval; Cluster analysis; Multimedia; Video retrieval; Annotation; Content (measure theory); Empirical research; World Wide Web; 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":[0.0001664587,0.00004305152,0.0001200957,0.00003525813,0.00002362617,0.000009587002,0.0005390574,0.00001663255,0.00002431274],"category_scores_gemma":[0.00004650413,0.00001719989,0.00004860167,0.0002261042,0.00002618935,0.0001488841,0.0001234659,0.00001857645,0.000001555474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006857908,"about_ca_system_score_gemma":0.00002718622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001230396,"about_ca_topic_score_gemma":0.0004848857,"domain_scores_codex":[0.9992162,0.0001054071,0.0002441287,0.0001377592,0.0002358578,0.00006066366],"domain_scores_gemma":[0.9991965,0.00005254024,0.00009024455,0.0005000065,0.0001343142,0.00002637628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008678765,0.00258019,0.8880011,0.000002495329,0.00006053905,6.349704e-7,0.00129426,0.00007929187,0.03411714,0.008093467,0.000425225,0.06533697],"study_design_scores_gemma":[0.0006594931,0.0006134421,0.9637635,0.00001097642,0.00001934948,5.127461e-7,0.0008537191,0.02782808,0.005845032,0.0002433341,0.000095198,0.0000673531],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7660206,0.000002845529,0.2328254,0.0009139752,0.00002709914,0.00007284054,0.000001465682,0.00001029766,0.0001255359],"genre_scores_gemma":[0.9986787,0.0000010465,0.0008269533,0.0001391846,0.00001170807,0.000001042566,3.075788e-7,0.000001466089,0.0003395328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2326582,"threshold_uncertainty_score":0.1001712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05625527980580385,"score_gpt":0.3124358080669544,"score_spread":0.2561805282611506,"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."}}