{"id":"W4409884910","doi":"10.1145/3706598.3713777","title":"A Multimodal Approach for Targeting Error Detection in Virtual Reality Using Implicit User Behavior","year":2025,"lang":"en","type":"article","venue":"","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Virtual reality; Human–computer interaction; Augmented reality; Artificial intelligence; 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":[0.0008855812,0.0008418137,0.0004822449,0.0008589808,0.0001478335,0.0005935715,0.000559183,0.0005835342,0.001179209],"category_scores_gemma":[0.005852201,0.0002467188,0.0004250231,0.0003513915,0.0002285795,0.0007240067,0.0008563518,0.0007363289,0.0004267559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003523231,"about_ca_system_score_gemma":0.0003978555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004555551,"about_ca_topic_score_gemma":0.006595355,"domain_scores_codex":[0.9993382,0.0002296511,0.0000321867,0.0001869457,0.0001501156,0.00006285249],"domain_scores_gemma":[0.9982132,0.0008328527,0.0002784317,0.0002017719,0.0003901961,0.00008360697],"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":[0.001652102,0.0007956616,0.04592733,0.0004411069,0.0003245896,0.0004409286,0.001249514,0.1708787,0.08729188,0.001761385,0.002922968,0.6863139],"study_design_scores_gemma":[0.00001628152,0.0004098353,0.01666793,0.00003554292,0.00004838306,0.0002177384,0.00007085886,0.9726858,0.007980635,0.001053774,0.0007678241,0.00004538367],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3360401,0.000652071,0.6568035,0.0003018962,0.00005065263,0.0001211899,0.0005387136,0.003405441,0.002086341],"genre_scores_gemma":[0.94258,0.0001572867,0.05563053,0.00006860953,0.00001865636,0.00007037548,0.0002577235,0.00006263941,0.001154179],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004555551,"threshold_uncertainty_score":0.009058058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03731748132287863,"score_gpt":0.3204038280260479,"score_spread":0.2830863467031692,"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."}}