{"id":"W4245967622","doi":"10.1109/vr46266.2020.00048","title":"Disambiguation Techniques for Freehand Object Manipulations in Virtual Reality","year":2020,"lang":"en","type":"article","venue":"2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Virtual reality; Object (grammar); Human–computer interaction; Gaze; Gesture; Context (archaeology); Set (abstract data type); Computer vision; Ambiguity; Augmented reality; Virtual image; Artificial intelligence; Optical head-mounted display; Modalities; Interaction technique","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":[0.0007924776,0.001009086,0.001001483,0.0008461077,0.0005530986,0.0008394187,0.0008903956,0.0006776794,0.002161301],"category_scores_gemma":[0.003565479,0.0004939105,0.0005428065,0.0004482064,0.0008204842,0.001355777,0.001754001,0.0005435676,0.0006219521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002036045,"about_ca_system_score_gemma":0.0002930368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006170342,"about_ca_topic_score_gemma":0.0007958505,"domain_scores_codex":[0.9986512,0.0003471135,0.00009728416,0.0003322101,0.0004239879,0.0001483092],"domain_scores_gemma":[0.9980611,0.001204986,0.0002506305,0.0002887988,0.0001157049,0.00007870263],"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":[0.001584173,0.0001149938,0.0006113719,0.0004904312,0.00005210839,0.0003010502,0.001166379,0.002913573,0.7504726,0.001900581,0.0004966363,0.2398961],"study_design_scores_gemma":[0.0001599574,0.002534378,0.01911637,0.0001179,0.0001834725,0.003231096,0.0008235673,0.03931729,0.913922,0.003794354,0.01646565,0.0003340488],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4150527,0.004158423,0.5752713,0.0001132016,0.0001538355,0.000274705,0.0001429592,0.002917549,0.001915236],"genre_scores_gemma":[0.7344497,0.001056215,0.262036,0.0001008887,0.00005589924,0.0001330723,0.0001465051,0.0002199671,0.001801872],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002161301,"threshold_uncertainty_score":0.007230222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1160353124808379,"score_gpt":0.3337115264111553,"score_spread":0.2176762139303174,"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."}}