{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000668907,0.0007430433,0.000471739,0.0005391851,0.0003640472,0.001290832,0.0006092725,0.0007743321,0.002338896],"category_scores_gemma":[0.006658159,0.0004170515,0.000412499,0.000302251,0.0005474222,0.002174233,0.001215786,0.0005194395,0.000833608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003374829,"about_ca_system_score_gemma":0.0004064658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005041387,"about_ca_topic_score_gemma":0.006622927,"domain_scores_codex":[0.9993519,0.0002245173,0.00003689138,0.0001889043,0.0001148018,0.0000828811],"domain_scores_gemma":[0.997961,0.001362569,0.0001819299,0.0001591516,0.0002243888,0.0001110246],"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":[0.001779251,0.0006263302,0.05131391,0.001149847,0.0001677663,0.001999818,0.009336959,0.1129142,0.3118907,0.005599253,0.004318351,0.4989035],"study_design_scores_gemma":[0.00004998541,0.000629033,0.07394847,0.0001499381,0.00006856921,0.0008039204,0.003302174,0.8747234,0.03042462,0.006028385,0.009715028,0.0001565203],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5887163,0.0004040943,0.3998843,0.0002620048,0.00005972571,0.0003158297,0.0002922521,0.00322592,0.00683951],"genre_scores_gemma":[0.9300991,0.0001789017,0.06795015,0.00006719367,0.000009041919,0.00008024715,0.0002304853,0.0002055274,0.001179394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005041387,"threshold_uncertainty_score":0.01002407,"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."}}