{"id":"W4308990711","doi":"10.1145/3567710","title":"Leveraging Smartwatch and Earbuds Gesture Capture to Support Wearable Interaction","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada); University of Waterloo","funders":"","keywords":"Gesture; Smartwatch; Wearable computer; Computer science; Human–computer interaction; Set (abstract data type); Context (archaeology); Wearable technology; Gesture recognition; Artificial intelligence; Embedded system","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":[],"consensus_categories":[],"category_scores_codex":[0.0003453713,0.0002630081,0.0002567778,0.0003270952,0.000651856,0.0002947101,0.002055452,0.00005338724,0.000100317],"category_scores_gemma":[0.00008481661,0.0002245411,0.0001565789,0.0004228741,0.0000301966,0.001300194,0.002920047,0.0008150472,0.00002885547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003130574,"about_ca_system_score_gemma":0.00002515775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001181648,"about_ca_topic_score_gemma":0.000003039891,"domain_scores_codex":[0.9981331,0.00003933683,0.0003577531,0.0006470497,0.0004977209,0.0003250294],"domain_scores_gemma":[0.998633,0.00009198138,0.0003693778,0.0005265378,0.0002947066,0.00008438905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005935308,0.0008562068,0.006500352,0.000207745,0.0003314327,0.00001467593,0.04473818,0.002259581,0.6754069,0.01128315,0.2379403,0.01986787],"study_design_scores_gemma":[0.003321692,0.007802735,0.09751585,0.001349027,0.0001930562,0.001738738,0.01524707,0.0359489,0.6452317,0.0122892,0.1767235,0.002638599],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826449,0.00001294365,0.001943347,0.007161791,0.002937769,0.0004601855,0.000004391474,0.00006245164,0.004772279],"genre_scores_gemma":[0.9935552,0.000002873214,0.002068458,0.00292174,0.0002168722,0.00006438376,0.000003251948,0.00002366754,0.00114355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0910155,"threshold_uncertainty_score":0.9156522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03947325581111828,"score_gpt":0.2992554450309514,"score_spread":0.2597821892198331,"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."}}