{"id":"W4401511223","doi":"10.3390/s24165168","title":"SmartVR Pointer: Using Smartphones and Gaze Orientation for Selection and Navigation in Virtual Reality","year":2024,"lang":"en","type":"article","venue":"Sensors","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Pointer (user interface); Computer science; Gaze; Laser pointer; Virtual reality; Computer vision; Human–computer interaction; Phone; Mobile phone; Optical head-mounted display; Artificial intelligence; Computer graphics (images)","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":[0.0005584506,0.0008299075,0.00043191,0.0007056934,0.0002519959,0.0008648583,0.00112819,0.00096642,0.008383433],"category_scores_gemma":[0.001783014,0.0004274489,0.0006368413,0.0003577193,0.0003595416,0.001629014,0.002008607,0.0005449701,0.00248917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002099746,"about_ca_system_score_gemma":0.0004130229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003649099,"about_ca_topic_score_gemma":0.004179147,"domain_scores_codex":[0.9994331,0.0001116385,0.00003722497,0.0001236445,0.0002227939,0.00007159961],"domain_scores_gemma":[0.9993021,0.0001658353,0.00006799171,0.0001304591,0.0002571367,0.00007636134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008199639,0.0002099225,0.006014924,0.001145745,0.000155351,0.001386008,0.002295813,0.003319302,0.2589345,0.008824401,0.02306021,0.6938339],"study_design_scores_gemma":[0.0008005613,0.005670432,0.06406699,0.001166212,0.0009622842,0.01543454,0.001924273,0.1917649,0.2578941,0.009253361,0.4494592,0.001603082],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1003575,0.003382918,0.8502094,0.0005453446,0.0003935878,0.0005384753,0.000881639,0.02516248,0.01852867],"genre_scores_gemma":[0.5302002,0.002985075,0.4389129,0.0008359415,0.0001874819,0.0006897972,0.001230143,0.001106562,0.02385176],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008383433,"threshold_uncertainty_score":0.02804536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02127685964199727,"score_gpt":0.3094027750414207,"score_spread":0.2881259153994234,"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."}}