{"id":"W7115035878","doi":"","title":"Assessing Deep Learning Techniques for Ice Hockey Human Activity Recognition from Game Simulated IMU Data: A Comparative Analysis of CNN, Transformer, and Hybrid Models","year":2025,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Bishop's University; McGill University","keywords":"Deep learning; Ice hockey; Activity recognition; Inertial measurement unit; Key (lock)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009965444,0.0006304279,0.001305635,0.001497028,0.001286685,0.0005408333,0.0009753337,0.0004881545,0.00003486291],"category_scores_gemma":[0.0001903258,0.000719025,0.0003861318,0.001355901,0.00005025076,0.005973823,0.0001476794,0.001157087,0.000004148584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002530915,"about_ca_system_score_gemma":0.0000678875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009344522,"about_ca_topic_score_gemma":0.00227051,"domain_scores_codex":[0.9958125,0.0005530133,0.0009612572,0.00159951,0.0006242762,0.0004494379],"domain_scores_gemma":[0.9961427,0.0008322246,0.00110487,0.0007879851,0.0009693825,0.0001627668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002505266,0.0004120291,0.000006693848,0.000434427,0.002758536,0.00001000051,0.0001593116,0.001243628,0.1007464,0.002303332,0.000001642582,0.8916734],"study_design_scores_gemma":[0.001528401,0.0003374435,0.0008355072,0.00135015,0.00510907,0.000003523586,0.0006714059,0.2854916,0.6267123,0.075105,0.001218007,0.001637657],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774905,0.0001496674,0.01219393,0.000007058787,0.0002123915,0.001042272,0.002698568,0.0004230704,0.005782575],"genre_scores_gemma":[0.9759721,0.0002076763,0.007039046,0.00005050049,0.00002620826,0.00009550264,0.01634673,0.00004204531,0.0002202201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8900357,"threshold_uncertainty_score":0.9995261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09008212106920808,"score_gpt":0.3408434281686648,"score_spread":0.2507613070994567,"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."}}