{"id":"W4237464509","doi":"10.32920/ryerson.14664657.v1","title":"Robust video event recognition","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Event (particle physics); Video quality; Quality (philosophy); Artificial intelligence; Feature (linguistics); Feature extraction; Video tracking; Computer vision; Machine learning; Video processing","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":[0.0003302947,0.0001584888,0.0002428499,0.0001324813,0.00006711263,0.000677132,0.0005983452,0.0001813263,0.0003574905],"category_scores_gemma":[0.00006275828,0.0001479441,0.0002356378,0.0002925967,0.000008388787,0.0002777379,0.001253842,0.0002511986,0.0000882867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006328642,"about_ca_system_score_gemma":0.0001574721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001601563,"about_ca_topic_score_gemma":0.0001684321,"domain_scores_codex":[0.998429,0.0001182949,0.0003362611,0.0006495749,0.0003138742,0.0001530082],"domain_scores_gemma":[0.9986746,0.0000302428,0.0001507392,0.0008021411,0.0002739681,0.00006826802],"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":[0.000004295182,0.0004714069,0.001185171,0.0002627623,0.0005061331,0.0001102199,0.001258931,0.1627422,0.0004999132,0.01229674,0.01760049,0.8030617],"study_design_scores_gemma":[0.0001305003,0.00001704522,0.001330754,0.0001776806,0.000062475,0.000005807417,0.00005696038,0.9826394,0.002024334,0.01188417,0.001193073,0.0004777915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003645319,0.0001726096,0.9869678,0.001263052,0.0007166485,0.0001036841,0.000002126517,0.0001572632,0.006971498],"genre_scores_gemma":[0.6605467,0.0005387247,0.3325592,0.001551004,0.0003510856,0.00007582434,0.0008959345,0.00002323144,0.003458231],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8198972,"threshold_uncertainty_score":0.6529599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0507210079655977,"score_gpt":0.2456321487700163,"score_spread":0.1949111408044186,"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."}}