{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004127385,0.0006784167,0.0004796114,0.0005421627,0.0002043243,0.0005273148,0.001508995,0.000589488,0.01369236],"category_scores_gemma":[0.001312533,0.0003964493,0.0006095393,0.0003566755,0.0002518028,0.0007245429,0.001075077,0.0005085671,0.002369617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002311366,"about_ca_system_score_gemma":0.0002832945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002223264,"about_ca_topic_score_gemma":0.003338936,"domain_scores_codex":[0.9992736,0.00008952816,0.00004713108,0.0001400007,0.000378043,0.00007166346],"domain_scores_gemma":[0.9992074,0.0002693643,0.0000522785,0.0001944096,0.0002190666,0.00005744041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005263874,0.0001977033,0.001390472,0.0006746748,0.00006615491,0.0007482845,0.0005294358,0.003586682,0.5269132,0.002697576,0.007720387,0.4549491],"study_design_scores_gemma":[0.0006032301,0.003834821,0.02051357,0.0002561462,0.0003125776,0.007110425,0.0003693938,0.2116625,0.5663963,0.001698241,0.1866712,0.0005716221],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07016785,0.001047336,0.9041988,0.0001685651,0.0002359471,0.0006574686,0.0004340298,0.009597605,0.01349232],"genre_scores_gemma":[0.3980801,0.0007163069,0.5825287,0.0003166989,0.0000806481,0.0004356948,0.0006432916,0.0006451384,0.01655344],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01369236,"threshold_uncertainty_score":0.04580545,"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."}}