{"id":"W2969532307","doi":"10.1109/ismar.2019.00027","title":"Performance Envelopes of Virtual Keyboard Text Input Strategies in Virtual Reality","year":2019,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":138,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Engineering and Physical Sciences Research Council","keywords":"Text entry; Computer science; Virtual keyboard; USable; Augmented reality; Human–computer interaction; Virtual reality; Decoding methods; Input device; Words per minute; Multimedia; Computer hardware","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":[],"consensus_categories":[],"category_scores_codex":[0.0002098487,0.0001263876,0.0002031563,0.0001299567,0.00002617854,0.00005247982,0.0006143054,0.00005299532,0.000177223],"category_scores_gemma":[0.00001677119,0.0001054565,0.0000522943,0.0002657145,0.00005247079,0.001607068,0.0002192875,0.0001441021,0.000351167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003880126,"about_ca_system_score_gemma":0.0001326448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002125022,"about_ca_topic_score_gemma":0.0000445875,"domain_scores_codex":[0.9989379,0.00005695629,0.0002671285,0.0002928801,0.0002144425,0.0002306972],"domain_scores_gemma":[0.9993062,0.00009389737,0.00008794445,0.0003670942,0.0001105102,0.00003437547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002258665,0.0004120651,0.06695521,0.00008368408,0.00005882636,0.00001171925,0.009491765,0.004809657,0.1875973,0.7049698,0.003279012,0.02210505],"study_design_scores_gemma":[0.001335788,0.001805506,0.6490096,0.0001465852,0.000005253556,0.00001101653,0.007266899,0.08418253,0.2515936,0.0005975525,0.003404013,0.0006416367],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8855155,0.000006273457,0.02606282,0.0002020776,0.0002680309,0.0001150034,0.000002357508,0.00001271264,0.08781522],"genre_scores_gemma":[0.9977719,0.00001577759,0.0003927234,0.0002340998,0.00001573515,0.000004024068,0.00000279327,0.000004466729,0.00155855],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7043722,"threshold_uncertainty_score":0.4513659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01370182321593653,"score_gpt":0.2551527536923265,"score_spread":0.24145093047639,"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."}}