{"id":"W2359451902","doi":"","title":"Vehicle Voice Navigation System's Research Based on SPCE061A Microcomputer","year":2009,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Radio-frequency identification; Dedicated short-range communications; Navigation system; Radio navigation; Identification (biology); Real-time computing; Intelligent transportation system; Microcomputer; Telecommunications; Global Positioning System; Embedded system; Computer security; Wireless; Transport engineering; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003023885,0.0004017173,0.0004499174,0.0005497259,0.0003457225,0.0005677043,0.0008943356,0.0004753561,0.00621392],"category_scores_gemma":[0.0005846019,0.0001828618,0.0002828505,0.0005100783,0.000183368,0.0008183612,0.0002549913,0.0003869233,0.0015697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005931652,"about_ca_system_score_gemma":0.0006088989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002896858,"about_ca_topic_score_gemma":0.001930413,"domain_scores_codex":[0.9994361,0.00009990013,0.00001838485,0.00009434338,0.0003130133,0.00003827612],"domain_scores_gemma":[0.9996368,0.00006474371,0.00001468225,0.00004232437,0.0002204252,0.00002104099],"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":[0.000849357,0.0003566448,0.00969875,0.00115743,0.0001873945,0.0005559512,0.000565499,0.03957092,0.1986531,0.02843041,0.0357511,0.6842235],"study_design_scores_gemma":[0.0002899676,0.001950298,0.009584499,0.0001732104,0.0003399089,0.002010239,0.0002069099,0.4181556,0.2711113,0.002411902,0.2936135,0.0001527908],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2199764,0.007348686,0.6480124,0.001102962,0.001015256,0.0005329085,0.0005343884,0.01042544,0.1110516],"genre_scores_gemma":[0.7942575,0.003610658,0.1118847,0.0003640235,0.0001662319,0.0003125928,0.001003443,0.0003023917,0.08809853],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00621392,"threshold_uncertainty_score":0.02078766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02481432350804301,"score_gpt":0.2995704284197177,"score_spread":0.2747561049116747,"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."}}