{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006752635,0.0003135479,0.0004816154,0.0001110171,0.000163579,0.000413028,0.0005831589,0.000219264,0.00002946031],"category_scores_gemma":[0.0003223464,0.0002894525,0.00008120521,0.0003924209,0.0001151457,0.0006997382,0.0001524694,0.0003263077,0.00003709857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000070242,"about_ca_system_score_gemma":0.0001340529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003210671,"about_ca_topic_score_gemma":0.001274762,"domain_scores_codex":[0.997425,0.0003528712,0.0006588278,0.0008517634,0.0003755537,0.0003359965],"domain_scores_gemma":[0.9985306,0.0003712909,0.0002230093,0.0004290614,0.0002149141,0.0002311495],"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":[0.001138545,0.0008180637,0.001084461,0.0005696299,0.0002163529,0.00006022239,0.03102535,0.001401953,0.02562021,0.1846449,0.01145225,0.7419681],"study_design_scores_gemma":[0.004355304,0.008372863,0.01052656,0.001779232,0.0001344685,0.00004788001,0.003656304,0.7743478,0.1368346,0.01697641,0.03996629,0.003002311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05769786,0.00004965355,0.9296647,0.007195106,0.0004376507,0.001219599,0.0002414492,0.0003467595,0.003147185],"genre_scores_gemma":[0.9974784,0.0001306864,0.0009906257,0.0007866553,0.0001883494,0.0001771447,0.00005523226,0.000016558,0.0001763833],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9397805,"threshold_uncertainty_score":0.9999558,"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."}}