{"id":"W4312736179","doi":"10.1109/ismar-adjunct57072.2022.00053","title":"Elicitation of Interaction Techniques with 3D Data Visualizations in Immersive Environment using HMDs","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Usability; Human–computer interaction; Computer science; Visualization; Set (abstract data type); Data visualization; Data exploration; Artificial intelligence","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":[0.003397336,0.000805139,0.0004242556,0.001270286,0.0006350221,0.001226732,0.000510737,0.0008451999,0.002536875],"category_scores_gemma":[0.01592644,0.0003090965,0.0005334472,0.0008959754,0.0006587991,0.001101838,0.001756324,0.00082095,0.0005138176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003990617,"about_ca_system_score_gemma":0.00069705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006084577,"about_ca_topic_score_gemma":0.001962525,"domain_scores_codex":[0.9950737,0.002794837,0.0003855062,0.0004562116,0.001055689,0.0002339626],"domain_scores_gemma":[0.9846325,0.01118891,0.0009363329,0.001195036,0.001805679,0.0002415488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"qualitative","study_design_scores_codex":[0.0006212806,0.0005052208,0.01437883,0.003971649,0.00008608873,0.001270871,0.08452953,0.003080633,0.5749938,0.010603,0.002695083,0.303264],"study_design_scores_gemma":[0.0003543588,0.003790647,0.1268146,0.001725949,0.000355722,0.005468495,0.06944495,0.05335295,0.5916052,0.01569976,0.1309412,0.0004463449],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5155694,0.0008920528,0.4669054,0.0005743953,0.00005679458,0.001020045,0.0008065099,0.0008047985,0.01337063],"genre_scores_gemma":[0.581199,0.0007874616,0.4123468,0.0001927244,0.00003136478,0.001224268,0.0004789247,0.0001384498,0.003600951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003397336,"threshold_uncertainty_score":0.01796705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0437940729831709,"score_gpt":0.3133249968217756,"score_spread":0.2695309238386047,"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."}}