{"id":"W2377608189","doi":"","title":"Interaction between Computers and Persons by Voice in tbe Ms Agent and C","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Dialog box; Human–computer interaction; Multimedia; Speech recognition; Natural language processing; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007440717,0.0001728532,0.0001777636,0.0001513322,0.0002929778,0.00008707957,0.0003960162,0.00006115837,0.000001119332],"category_scores_gemma":[4.782055e-7,0.0001896022,0.00003296153,0.0004118409,0.0001025282,0.000359586,0.0003117016,0.0001855001,0.00001567484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006206799,"about_ca_system_score_gemma":0.00002263616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004634047,"about_ca_topic_score_gemma":0.000003997691,"domain_scores_codex":[0.9987921,0.00002917859,0.0002811665,0.0005687762,0.0001140087,0.0002147519],"domain_scores_gemma":[0.9992976,0.0001631534,0.0000969768,0.0002745089,0.00004636834,0.0001213972],"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":[0.000005866764,0.0005336148,0.01350752,0.00006787121,0.00006926993,0.00001081673,0.003646156,0.000698917,0.01130044,0.05062782,0.03136852,0.8881632],"study_design_scores_gemma":[0.0006742117,0.00007571554,0.03551777,0.00003950068,0.00001154494,0.0002690212,0.00003642993,0.04018866,0.001943417,0.01047837,0.9101597,0.0006056543],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03360496,0.0001939642,0.9632637,0.001962898,0.00001017244,0.0005674735,0.00002250074,0.0002138868,0.0001604356],"genre_scores_gemma":[0.3316205,0.0001420188,0.6669062,0.0006758217,0.0000806567,0.0004403511,0.0000578501,0.00001459945,0.00006197575],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8875575,"threshold_uncertainty_score":0.7731755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01854342430098955,"score_gpt":0.2772785540826571,"score_spread":0.2587351297816676,"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."}}