{"id":"W2988878602","doi":"10.1145/3359996.3364265","title":"HawKEY: Efficient and Versatile Text Entry for Virtual Reality","year":2019,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Text entry; Computer science; Human–computer interaction; Virtual reality; Visualization; Task (project management); Virtual keyboard; Multimedia; Artificial intelligence; Computer hardware; Engineering","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":[0.0001016,0.00006897039,0.0000836175,0.00003082239,0.0000501341,0.00005580517,0.0001939497,0.00002640612,0.00009624691],"category_scores_gemma":[0.00002040751,0.00005642964,0.00004103431,0.00005473012,0.00001743844,0.0001780432,0.0001227797,0.00004279862,0.0001975823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002222952,"about_ca_system_score_gemma":0.00002157383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003185301,"about_ca_topic_score_gemma":0.000001993166,"domain_scores_codex":[0.9994014,0.00001671206,0.0000820089,0.0002491781,0.00009057065,0.0001601617],"domain_scores_gemma":[0.9995097,0.0001338361,0.00003024383,0.0002193569,0.00006434847,0.00004254679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001575988,0.0002676806,0.002457398,0.00004683141,0.0000768969,0.000003432025,0.003637792,0.0004116365,0.07591305,0.8182994,0.08585709,0.01287127],"study_design_scores_gemma":[0.003554776,0.001552046,0.05642126,0.00005819203,0.00002265095,0.00001964307,0.002554177,0.6401329,0.1879709,0.001503346,0.1054266,0.0007835469],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2937557,0.00002053556,0.6490849,0.001500601,0.0007872786,0.000387193,0.00001203266,0.00002498819,0.05442683],"genre_scores_gemma":[0.9952685,0.000001521989,0.0008782866,0.000806027,0.00002193024,0.000006329874,0.000003413991,0.000003092733,0.003010955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.816796,"threshold_uncertainty_score":0.2539587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0108014212268782,"score_gpt":0.2541610966973473,"score_spread":0.2433596754704691,"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."}}