{"id":"W4293798002","doi":"10.1155/2022/8369362","title":"Multicriteria Model for Shared Parking and Parking Route Recommender Systems","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Beijing University of Civil Engineering and Architecture; Beijing Municipal Natural Science Foundation; Beijing Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Parking space; Analytic hierarchy process; Transport engineering; Parking guidance and information; Computer science; TOPSIS; Economic shortage; Entropy (arrow of time); Operations research; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005146586,0.0001171511,0.0002510089,0.0001784703,0.0001432078,0.00004685533,0.0001121888,0.0000324836,0.00000760133],"category_scores_gemma":[0.00001766563,0.0001261282,0.000073797,0.000117028,0.00000839645,0.0003657423,0.000003762944,0.0002296113,1.580619e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001646343,"about_ca_system_score_gemma":0.00002771226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000471434,"about_ca_topic_score_gemma":0.00001261117,"domain_scores_codex":[0.9987584,0.00003803776,0.0005726311,0.0001171602,0.0003021641,0.0002116151],"domain_scores_gemma":[0.9994243,0.0001173136,0.0001811228,0.00008738128,0.0001181884,0.00007165063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001170626,0.00001271494,0.001069766,0.0002474844,0.00006138781,0.000008830585,0.003128602,0.9774598,0.01510206,0.00004023711,0.0002240278,0.002527993],"study_design_scores_gemma":[0.001911175,0.0001188581,0.008002171,0.0001794451,0.00004681554,0.00004091649,0.001924689,0.9745719,0.0003461431,0.0001388394,0.01250491,0.0002140966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8157575,0.001407216,0.1805437,0.00005934594,0.001529932,0.0004808178,0.0001257678,0.00006265268,0.00003306557],"genre_scores_gemma":[0.9901934,0.00007871264,0.009378621,0.00001073048,0.0001192467,0.00009789963,0.00003877944,0.00004469055,0.00003796607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1744358,"threshold_uncertainty_score":0.5143359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03203348039684355,"score_gpt":0.281004985687097,"score_spread":0.2489715052902535,"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."}}