{"id":"W2738617613","doi":"10.1109/cvprw.2017.24","title":"Classification of Puck Possession Events in Ice Hockey","year":2017,"lang":"en","type":"article","venue":"","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Western Canada Research Grid; Compute Canada","keywords":"Ice hockey; Computer science; Possession (linguistics); Convolutional neural network; Context (archaeology); Artificial intelligence; Frame (networking); Machine learning; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001279426,0.00003644135,0.00005436995,0.0000651805,0.00009360764,0.0000364003,0.0003724984,0.00003053284,0.00003972007],"category_scores_gemma":[0.00002922732,0.0000313936,0.00001912084,0.00004317171,0.00001175401,0.0007297348,0.00006681698,0.00004270468,0.00008415263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001337278,"about_ca_system_score_gemma":0.00001886169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007726561,"about_ca_topic_score_gemma":0.00006129237,"domain_scores_codex":[0.9995565,0.00002117877,0.0001236375,0.0001258321,0.0001060831,0.00006675562],"domain_scores_gemma":[0.9994232,0.00001401188,0.0001304065,0.0003662718,0.00004491851,0.00002121064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002697733,0.0007831233,0.2110135,0.00007392331,0.00001717521,0.000007243581,0.0009444454,0.00001833338,0.1088001,0.1105221,0.002443145,0.5653499],"study_design_scores_gemma":[0.0002422123,0.00001934708,0.9719779,0.00003653259,9.404476e-7,0.000001294674,0.0000234643,0.008142514,0.01365859,0.005522088,0.0003199426,0.00005513618],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9177322,0.000004168024,0.05312067,0.0008557092,0.0002135202,0.00008043218,4.184235e-7,0.0000319009,0.02796094],"genre_scores_gemma":[0.9977729,0.000008233709,0.001490908,0.00004389172,0.00001770333,0.000003788871,0.000001574236,0.000001580306,0.0006594461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7609645,"threshold_uncertainty_score":0.1280194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05282793142282936,"score_gpt":0.3210927505957971,"score_spread":0.2682648191729677,"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."}}