{"id":"W2379406935","doi":"","title":"A Study on Integrated Map Matching Technology in Vehicle Positioning System","year":2010,"lang":"en","type":"article","venue":"Modern Radar","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Combing; Computation; Map matching; Matching (statistics); Computer science; Positioning technology; Blossom algorithm; Real-time computing; State (computer science); Range (aeronautics); Algorithm; Simulation; Engineering; Global Positioning System; Geography; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001144405,0.0001025622,0.0001116374,0.0003134643,0.00004270921,0.00002754791,0.0001312564,0.00008261818,0.000002563672],"category_scores_gemma":[0.000002759327,0.0001038604,0.0000165117,0.0001681648,0.00001121306,0.00006829793,0.00002684038,0.0003927277,0.00002444907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007520335,"about_ca_system_score_gemma":0.000003836532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002971916,"about_ca_topic_score_gemma":0.00009572393,"domain_scores_codex":[0.9994556,0.00001259178,0.0001487311,0.0001421261,0.00009271908,0.0001482366],"domain_scores_gemma":[0.9997467,0.000007437952,0.00001403655,0.0001996691,0.000009735325,0.00002240771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001220544,0.001657693,0.01159437,0.0005685262,0.0004031055,0.001075327,0.013785,0.04469619,0.611097,0.1189659,0.009218115,0.1868168],"study_design_scores_gemma":[0.002817774,0.0004415201,0.01525423,0.0005563677,0.00005037319,0.0000457871,0.01190358,0.9393693,0.02275387,0.002995086,0.002902494,0.0009096368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9085237,0.00001477171,0.08040978,0.000116135,0.0003029757,0.0003097518,0.000002834406,0.007958529,0.002361506],"genre_scores_gemma":[0.9984,8.412047e-7,0.001453714,0.00001780405,0.00001916704,0.00005919561,0.000003358156,0.00002445136,0.00002151776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8946731,"threshold_uncertainty_score":0.4235305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005502486765981086,"score_gpt":0.2086343829909077,"score_spread":0.2031318962249266,"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."}}