{"id":"W4407950258","doi":"10.1109/aixvr63409.2025.00036","title":"Towards Skeleton Based Keystroke Recognition in Virtual Reality","year":2025,"lang":"en","type":"article","venue":"","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Virtual reality; Skeleton (computer programming); Keystroke logging; Human–computer interaction; Artificial intelligence; Keystroke dynamics; Computer vision; Computer security; Password; Programming language","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":[0.0004284884,0.00145752,0.00126581,0.002010368,0.0002696873,0.001078174,0.001126246,0.001225784,0.003142552],"category_scores_gemma":[0.002404983,0.0004446456,0.001098942,0.001205777,0.0004522801,0.001089293,0.001544056,0.001085458,0.004063718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003338442,"about_ca_system_score_gemma":0.0006469387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004605378,"about_ca_topic_score_gemma":0.008188572,"domain_scores_codex":[0.9991457,0.0001287647,0.00005100256,0.0003369435,0.0002073322,0.0001302023],"domain_scores_gemma":[0.9993314,0.0001635893,0.00008359915,0.000177265,0.0001773141,0.00006691185],"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":[0.0007908471,0.0002186026,0.003965771,0.0002667305,0.0001062665,0.0004941531,0.0001578973,0.03699173,0.09061544,0.002311988,0.01697405,0.8471066],"study_design_scores_gemma":[0.00004397524,0.0003421204,0.007697762,0.0001262212,0.00005447879,0.001258986,0.0002022064,0.9135036,0.05613245,0.006807892,0.0137432,0.00008710669],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0937138,0.002584766,0.8784836,0.0002707182,0.0002352105,0.0001757953,0.002990954,0.01757821,0.003966955],"genre_scores_gemma":[0.5453365,0.002283661,0.4346768,0.0002354612,0.0001119481,0.0002740282,0.008531871,0.0004666861,0.008083103],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004605378,"threshold_uncertainty_score":0.01051295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02812721692985811,"score_gpt":0.281484036824898,"score_spread":0.2533568198950399,"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."}}