{"id":"W4287178698","doi":"10.48550/arxiv.2105.10563","title":"Puck localization and multi-task event recognition in broadcast hockey\\n videos","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Event (particle physics); Context (archaeology); Artificial intelligence; Task (project management); Computer vision; Engineering; Geography","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002827827,0.0002331625,0.000314495,0.0004106439,0.0001121004,0.0002492907,0.0004674186,0.0002650257,0.00002198879],"category_scores_gemma":[0.0000648948,0.000286314,0.0001300964,0.0009449336,0.00004359702,0.0006106857,0.0009734012,0.0003125526,0.00001851974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001986261,"about_ca_system_score_gemma":0.0001332217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005413393,"about_ca_topic_score_gemma":0.0009098103,"domain_scores_codex":[0.9980711,0.0002669394,0.000287544,0.001049404,0.0001018567,0.0002231541],"domain_scores_gemma":[0.9988027,0.00003743456,0.0002336292,0.0005925468,0.0002227099,0.000110958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002958192,0.0005078187,0.06524892,0.0002422964,0.0001757085,0.000620226,0.001873632,0.8728809,0.0001911959,0.005342614,0.0001133405,0.05277377],"study_design_scores_gemma":[0.0005079404,0.00001875065,0.006018529,0.0001834614,0.00005744489,0.00000305013,0.0001635225,0.989493,0.00009291788,0.003037999,0.000100826,0.0003226039],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1913655,0.000153593,0.8078879,0.00006203839,0.0001804208,0.0001815252,0.000006340411,0.00006260767,0.0001000286],"genre_scores_gemma":[0.9960132,0.0009779746,0.002411705,0.0001173638,0.00002869622,0.000001547363,0.0001912159,0.00001189517,0.0002463899],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8054762,"threshold_uncertainty_score":0.9999589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06679461980108352,"score_gpt":0.1890348516065564,"score_spread":0.1222402318054729,"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."}}