{"id":"W2059136675","doi":"10.1145/1168987.1168992","title":"Indirect text entry using one or two keys","year":2006,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Huffman coding; Hierarchy; Text entry; Containment (computer programming); Coding (social sciences); Key (lock); Encoding (memory); Theoretical computer science; Artificial intelligence; Programming language; Human–computer interaction; Computer security; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00006208726,0.00009016675,0.0001029542,0.00007973651,0.00009038528,0.00009787799,0.000324493,0.00002415457,0.0004560572],"category_scores_gemma":[0.00001141731,0.0000701337,0.0000490833,0.0002322741,0.00001841694,0.0005119966,0.0001257976,0.00007496341,0.0003463158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004938242,"about_ca_system_score_gemma":0.00004839063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005880501,"about_ca_topic_score_gemma":0.00005544326,"domain_scores_codex":[0.99925,0.00003231966,0.0001214498,0.0002267463,0.0001424534,0.0002270157],"domain_scores_gemma":[0.9995788,0.00005676601,0.00004651183,0.0002200926,0.00006571707,0.00003213401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008491376,0.0007920326,0.009509017,0.0000224925,0.0001176206,0.0001709701,0.00080745,0.0003755021,0.7736667,0.1662966,0.03696195,0.01119465],"study_design_scores_gemma":[0.001034421,0.0001446099,0.02851687,0.00006041288,0.00002009543,0.00007439244,0.0001414586,0.0431808,0.9140134,0.002036869,0.01025124,0.0005253578],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1819093,0.00003996399,0.5861446,0.0002903005,0.0004247414,0.0001061528,0.000001609631,0.00004619895,0.2310372],"genre_scores_gemma":[0.974061,0.000001619772,0.01707067,0.0008307043,0.0001289808,0.000001910246,0.000002086698,0.000005754785,0.007897353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7921517,"threshold_uncertainty_score":0.4993507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02969157385854818,"score_gpt":0.2839925466615669,"score_spread":0.2543009728030187,"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."}}