{"id":"W4224274106","doi":"10.1109/vrw55335.2022.00142","title":"Multi-Touch Smartphone-Based Progressive Refinement VR Selection","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Selection (genetic algorithm); Gesture; Object (grammar); Computer graphics (images); Controller (irrigation); Artificial intelligence; Human–computer interaction; Computer vision","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004404779,0.0003635406,0.0003412692,0.0001691872,0.0007313291,0.000449642,0.0005269531,0.0001075468,0.0004395564],"category_scores_gemma":[0.00005762445,0.0003327302,0.00007458265,0.0002960919,0.0001447164,0.0005278779,0.00033604,0.0008450016,0.00002014354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001309805,"about_ca_system_score_gemma":0.0001495031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002873713,"about_ca_topic_score_gemma":0.0001871072,"domain_scores_codex":[0.9974341,0.0002510098,0.0004578637,0.0008944107,0.000489696,0.0004729072],"domain_scores_gemma":[0.9987026,0.0002052422,0.0003183788,0.0003794655,0.0001939605,0.0002003256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006509521,0.008804129,0.005115995,0.0004485586,0.001282148,0.0005017124,0.02851627,0.03769861,0.3273924,0.04807981,0.04671493,0.4889359],"study_design_scores_gemma":[0.01011019,0.01399621,0.1587806,0.001238877,0.0002594377,0.0002300188,0.01947582,0.4412162,0.2835819,0.001055494,0.06545797,0.004597316],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9714574,0.0002189798,0.0209636,0.003021272,0.00132758,0.0006331151,0.0001256958,0.00008554396,0.002166846],"genre_scores_gemma":[0.9967755,0.00009662432,0.0004622818,0.001255052,0.00005607721,0.000139708,0.00003798253,0.00001706073,0.001159697],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4843386,"threshold_uncertainty_score":0.9999125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04479860687999125,"score_gpt":0.300916472865882,"score_spread":0.2561178659858907,"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."}}