{"id":"W2131470614","doi":"10.1109/pacrim.1989.48400","title":"Evaluation of speech recognition equipment in a vehicular environment","year":2003,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Speech recognition; Preprocessor; Computer science; Noise (video); White noise; Artificial intelligence; Natural language processing; Pattern recognition (psychology); Telecommunications","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":[0.001681492,0.00004706631,0.00006034062,0.0000661784,0.00001553836,0.00001852887,0.0001008793,0.00002294354,0.0001754412],"category_scores_gemma":[0.00005947491,0.00004281306,0.00001751267,0.0001352722,0.000008726454,0.0002069867,0.00002393057,0.00003255004,0.00004707805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000915152,"about_ca_system_score_gemma":0.00006389256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006042351,"about_ca_topic_score_gemma":0.000003796846,"domain_scores_codex":[0.9989566,0.0001075872,0.0001470652,0.0001579833,0.0005263478,0.000104437],"domain_scores_gemma":[0.999724,0.00001180943,0.00004846954,0.0001453892,0.00004836455,0.00002198983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[6.735967e-7,0.00006686273,0.0003850149,0.000005249255,0.00000389478,0.000002192947,0.0001234912,0.0003807624,0.01974617,0.0001876608,0.00001644476,0.9790816],"study_design_scores_gemma":[0.000461466,0.000033378,0.001036268,0.00002322715,0.000007420366,0.000005188511,0.00003120847,0.01068998,0.9655454,0.02180984,0.0002838757,0.00007274977],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8240439,0.0002747545,0.1525793,0.0002174589,0.00007168375,0.0002242964,1.924213e-7,0.00002188526,0.02256652],"genre_scores_gemma":[0.8504828,0.00001282373,0.1493939,0.0000575383,0.000005868976,0.00001268601,8.750742e-7,0.000001930691,0.00003149346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9790089,"threshold_uncertainty_score":0.1920958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0520784317752567,"score_gpt":0.2697342812436163,"score_spread":0.2176558494683596,"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."}}