{"id":"W4293080612","doi":"10.1155/2022/8364988","title":"Research on Parking Service Optimization Based on Permit Reservation and Allocation","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Higher Education Discipline Innovation Project; National Natural Science Foundation of China","keywords":"Reservation; Service (business); Matching (statistics); Transport engineering; Genetic algorithm; Order (exchange); Parking guidance and information; Ant colony optimization algorithms; Computer science; Service level; Operations research; Mode (computer interface); Engineering; Business; Computer network","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":[0.00060818,0.0005932308,0.000813088,0.000471742,0.0004267085,0.0009558535,0.0007187264,0.000583581,0.001563218],"category_scores_gemma":[0.001265795,0.0003528232,0.0008544925,0.00104813,0.0005759496,0.001469973,0.0004818022,0.0007044416,0.0001244919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008104796,"about_ca_system_score_gemma":0.001548281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006485172,"about_ca_topic_score_gemma":0.004307195,"domain_scores_codex":[0.9995375,0.0001570387,0.00002133897,0.00009386775,0.00009779038,0.00009244914],"domain_scores_gemma":[0.9996206,0.0002039198,0.00004288601,0.00001870569,0.00008042577,0.0000334571],"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":[0.00008573639,0.00009785074,0.001535297,0.0002701398,0.00006899067,0.00009359467,0.0000853834,0.9247561,0.003236463,0.02684059,0.0009836936,0.04194604],"study_design_scores_gemma":[0.000007515162,0.00005819833,0.0003256566,0.000005627866,0.00001815762,0.00002732385,0.00005067839,0.9929581,0.0005461805,0.005159951,0.0008337468,0.000008988931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1672881,0.003163443,0.814391,0.0008835869,0.0001533648,0.0001051605,0.00007886026,0.0001969833,0.01373943],"genre_scores_gemma":[0.9540867,0.001967737,0.04018367,0.00008329884,0.0000604979,0.00004766765,0.00006170982,0.00004522479,0.003463475],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006485172,"threshold_uncertainty_score":0.01289481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04149149529610551,"score_gpt":0.3185259467043449,"score_spread":0.2770344514082393,"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."}}