{"id":"W4296784305","doi":"10.1145/3546736","title":"Understanding and Adapting Bezel-to-Bezel Interactions for Circular Smartwatches in Mobile and Encumbered Scenarios","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":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of Waterloo; Kelowna General Hospital; University of Manitoba; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Basic and Applied Basic Research Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Smartwatch; Computer science; Human–computer interaction; Gesture; Set (abstract data type); Control (management); Task (project management); Position (finance); Artificial intelligence; Embedded system; Wearable computer; Engineering","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":[0.0003920391,0.0002004998,0.0002414881,0.0003993836,0.0005911799,0.0002135249,0.0009729181,0.00003376127,0.00001004861],"category_scores_gemma":[0.0001338547,0.0001869895,0.0001083806,0.0003237892,0.00004091971,0.0009896938,0.001642893,0.0004056385,0.000001529647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003938589,"about_ca_system_score_gemma":0.00001692652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006825154,"about_ca_topic_score_gemma":0.00001580532,"domain_scores_codex":[0.9985397,0.00003056343,0.0003600258,0.000549226,0.0002471599,0.0002732915],"domain_scores_gemma":[0.9989014,0.0003007706,0.0003043759,0.0002907638,0.0001430025,0.00005973914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006146331,0.0009414132,0.01455394,0.0004411676,0.0003134905,0.000005447268,0.05024047,0.003564132,0.8585903,0.05023562,0.01052132,0.009978076],"study_design_scores_gemma":[0.00808976,0.008638631,0.06977673,0.003075717,0.0002518471,0.000938334,0.06609625,0.4633186,0.2739296,0.07609218,0.02657031,0.003222112],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775274,0.00002360471,0.01840094,0.001770878,0.000949572,0.0008739233,0.000007299123,0.00002860396,0.0004177181],"genre_scores_gemma":[0.9953065,0.000003632817,0.003742645,0.0005382535,0.00008270208,0.0002208672,0.000002415433,0.00001850924,0.00008450951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5846607,"threshold_uncertainty_score":0.7625211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1208075738564698,"score_gpt":0.3233394549235428,"score_spread":0.2025318810670729,"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."}}