{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006563403,0.001254667,0.0006852556,0.001109474,0.0003767375,0.0007232712,0.001129714,0.0007788088,0.001417402],"category_scores_gemma":[0.002379538,0.0002679757,0.0004397608,0.0005764005,0.0003804762,0.001252239,0.0009414662,0.001011462,0.0006554161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007195491,"about_ca_system_score_gemma":0.000413335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01250198,"about_ca_topic_score_gemma":0.01172254,"domain_scores_codex":[0.9994691,0.00008051925,0.00002022612,0.0002373803,0.00008093197,0.000111898],"domain_scores_gemma":[0.9994681,0.0002359773,0.00006265555,0.00006336093,0.000111488,0.00005829511],"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":[0.001234648,0.0006887537,0.01043976,0.0002765811,0.0001646672,0.0004978331,0.0003438583,0.1933896,0.04235084,0.00222782,0.009128752,0.739257],"study_design_scores_gemma":[0.00001058885,0.0001346482,0.004287186,0.00001217977,0.00002586865,0.00006600841,0.000120067,0.982754,0.01010348,0.001508187,0.0009669738,0.00001088836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4403914,0.001539023,0.5459778,0.0005296591,0.0003546154,0.000212749,0.001023986,0.004173751,0.005797034],"genre_scores_gemma":[0.9388961,0.0003195948,0.05450321,0.0001338552,0.0001244085,0.00007582382,0.001772482,0.00009253999,0.004081864],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01250198,"threshold_uncertainty_score":0.02485842,"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."}}