{"id":"W4416962810","doi":"10.1109/star66750.2025.11264776","title":"From IMUs to Smartwatches: Measuring Performance in Practical Shooting","year":2025,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Surgical Specialties (Canada)","funders":"Arm","keywords":"Wearable computer; Inertial measurement unit; Units of measurement; Activity recognition; Key (lock); Smartwatch; Athletes","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":[0.0002693207,0.0008640403,0.0004464145,0.0006464607,0.0001328277,0.0004344135,0.0004037078,0.0005710786,0.001880719],"category_scores_gemma":[0.0011302,0.0001585444,0.0001693898,0.0004221041,0.0001974194,0.0003928506,0.0004961689,0.0002087427,0.001155525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001043685,"about_ca_system_score_gemma":0.0001132646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006633407,"about_ca_topic_score_gemma":0.002496304,"domain_scores_codex":[0.9996719,0.00006825301,0.0000224981,0.0001033955,0.00009817023,0.00003571333],"domain_scores_gemma":[0.9996575,0.0001018925,0.00006579689,0.00003053089,0.00009359475,0.0000507458],"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":[0.003016867,0.0008534123,0.188307,0.001236909,0.0002744557,0.0005426176,0.001178263,0.008117927,0.2453794,0.0003963894,0.002801475,0.5478954],"study_design_scores_gemma":[0.000150995,0.006415698,0.7618893,0.0003135959,0.0002701559,0.001675523,0.002263386,0.1070736,0.1128694,0.001230333,0.005739535,0.0001084699],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9539654,0.0003233813,0.04031992,0.00007165668,0.00007544399,0.0001505738,0.0007186726,0.0005883867,0.00378655],"genre_scores_gemma":[0.9771095,0.0002371523,0.02054837,0.00007248895,0.00003963149,0.0001370109,0.0004043668,0.00003158501,0.00141984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001880719,"threshold_uncertainty_score":0.006291568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05530372425774568,"score_gpt":0.3006079167893671,"score_spread":0.2453041925316214,"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."}}