{"id":"W4248929594","doi":"10.32920/ryerson.14664657","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; Multimedia","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008853117,0.00137428,0.00150585,0.002729575,0.0003530309,0.001390729,0.001634042,0.001391648,0.003566698],"category_scores_gemma":[0.003914024,0.0003244705,0.001133499,0.001900408,0.0003597752,0.002082927,0.0009925347,0.001238186,0.005150504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004801755,"about_ca_system_score_gemma":0.0005137121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002059117,"about_ca_topic_score_gemma":0.001822577,"domain_scores_codex":[0.9985976,0.0001351429,0.0001069957,0.0005806495,0.0004368463,0.0001427899],"domain_scores_gemma":[0.9985307,0.0002623482,0.0002247039,0.0004286355,0.0004884928,0.00006501257],"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":[0.0004874392,0.0001746402,0.001780565,0.0004166752,0.0001391259,0.0003519708,0.00006047906,0.01777471,0.1126438,0.00427836,0.0186043,0.843288],"study_design_scores_gemma":[0.00006864915,0.0004497347,0.01037417,0.0001003859,0.0002164801,0.001372998,0.000195476,0.7120733,0.2191803,0.01309971,0.04275317,0.000115764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01701858,0.001431317,0.9669316,0.0002005857,0.0002947196,0.0003216104,0.00234473,0.007731586,0.003725255],"genre_scores_gemma":[0.3062655,0.002364055,0.6634872,0.0004213991,0.0005853368,0.0003894033,0.01527628,0.000845155,0.01036565],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003566698,"threshold_uncertainty_score":0.01193184,"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."}}