{"id":"W156197033","doi":"10.1007/978-0-387-68439-0_2","title":"User Interface Design for Natural Language Systems: From Research to Reality","year":2007,"lang":"en","type":"book-chapter","venue":"Signals and communication technology","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Tellabs (Canada)","funders":"","keywords":"Natural language user interface; Computer science; Natural (archaeology); Natural language; Interface (matter); Human–computer interaction; User interface; Natural language understanding; Center (category theory); Artificial intelligence; Programming language; History","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":[0.003934329,0.001120003,0.00121043,0.0008682614,0.0004803627,0.00564908,0.002902907,0.002424574,0.007317252],"category_scores_gemma":[0.009125681,0.0008087406,0.0006889406,0.0009640583,0.002645856,0.006337921,0.001464857,0.002331692,0.002278534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008538333,"about_ca_system_score_gemma":0.001042212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001112342,"about_ca_topic_score_gemma":0.0008430439,"domain_scores_codex":[0.9969457,0.001341079,0.000223747,0.0004189385,0.000953235,0.0001172406],"domain_scores_gemma":[0.9963455,0.002567213,0.00008277688,0.0003054046,0.0005896379,0.0001095992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001241993,0.0001169468,0.0005233026,0.002858261,0.00007337947,0.0001469311,0.003932646,0.004096045,0.01600121,0.1804937,0.03684717,0.7547862],"study_design_scores_gemma":[0.0001044826,0.0005500694,0.001365068,0.002715759,0.000131014,0.002046019,0.002081954,0.0695952,0.02156001,0.3079794,0.5916769,0.0001940685],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006976888,0.06664573,0.8960263,0.002759573,0.0005133792,0.0001254077,0.0001306366,0.002758277,0.0240639],"genre_scores_gemma":[0.1271204,0.04141885,0.7894337,0.001497167,0.0006646302,0.0004676851,0.0006026848,0.001344486,0.03745041],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007317252,"threshold_uncertainty_score":0.02447861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1216322296776337,"score_gpt":0.378101684247503,"score_spread":0.2564694545698693,"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."}}