{"id":"W2024952194","doi":"10.1109/smc.2013.638","title":"Use of Foot for Direct Interactions with Entities of a Virtual Environment Displayed on a Mobile Device","year":2013,"lang":"en","type":"article","venue":"","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wearable computer; Computer science; Interface (matter); Mobile device; Gesture; Human–computer interaction; Accelerometer; Wearable technology; Virtual machine; Mobile interaction; User interface; Embedded system; Artificial intelligence; World Wide Web; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002383857,0.0006906514,0.0003580831,0.0003889175,0.0003135725,0.001204698,0.0006340759,0.0006452884,0.006677798],"category_scores_gemma":[0.001056065,0.0001726545,0.0003768809,0.0002241431,0.0003849341,0.00110565,0.001588987,0.0002843788,0.001339064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006693516,"about_ca_system_score_gemma":0.0001335539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00025026,"about_ca_topic_score_gemma":0.0004221908,"domain_scores_codex":[0.9996468,0.00008948085,0.00002494385,0.00007908971,0.0001059925,0.00005379703],"domain_scores_gemma":[0.9994116,0.0002387201,0.00007258837,0.0001180504,0.00008391059,0.00007524309],"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":[0.0005913697,0.0001197556,0.003397033,0.001011779,0.00007334808,0.002914133,0.00114857,0.0005777847,0.658599,0.00448291,0.002979217,0.3241052],"study_design_scores_gemma":[0.0001984959,0.004207116,0.03598197,0.00106973,0.0007658973,0.02383583,0.00188257,0.0286762,0.6255149,0.005198167,0.2723047,0.000364415],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1902222,0.003785459,0.7780024,0.0004318068,0.000588499,0.0002315535,0.000380794,0.003134517,0.02322277],"genre_scores_gemma":[0.8049843,0.001663194,0.1764207,0.0003425821,0.0001501057,0.0001413182,0.0002570317,0.0001881758,0.01585267],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006677798,"threshold_uncertainty_score":0.02233946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03077589533455777,"score_gpt":0.2411548535851678,"score_spread":0.21037895825061,"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."}}