{"id":"W4404067741","doi":"10.3390/su16229615","title":"Urban Transportation Data Research Overview: A Bibliometric Analysis Based on CiteSpace","year":2024,"lang":"en","type":"article","venue":"Sustainability","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Regional science; Bibliometrics; Geography; Data science; Transport engineering; Computer science; Engineering; Library science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.00766577,0.001080121,0.001636647,0.245352,0.003204259,0.01054335,0.001155921,0.001313072,0.009139868],"category_scores_gemma":[0.04289547,0.0004137225,0.001588925,0.3058073,0.001857336,0.0106453,0.004333653,0.001378779,0.002364389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004131984,"about_ca_system_score_gemma":0.008008596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01084174,"about_ca_topic_score_gemma":0.01394388,"domain_scores_codex":[0.9887111,0.002006174,0.001942425,0.001047792,0.005802371,0.0004901941],"domain_scores_gemma":[0.9362491,0.03677223,0.006862311,0.002844776,0.01589342,0.001378112],"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":[0.000165299,0.0001329361,0.06637743,0.05092784,0.001108404,0.0008635315,0.007657885,0.003170455,0.002881031,0.1003618,0.1719055,0.594448],"study_design_scores_gemma":[0.00002157972,0.00007146362,0.06687099,0.01472938,0.0009900045,0.001081426,0.008453893,0.002989931,0.001823578,0.02349503,0.8792961,0.0001766282],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.08867231,0.4992355,0.02811587,0.0304433,0.003964578,0.0008782347,0.1340298,0.001822648,0.2128377],"genre_scores_gemma":[0.414067,0.4427768,0.03379007,0.002590073,0.004318055,0.001455061,0.08461007,0.0006922719,0.01570048],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.754648,"threshold_uncertainty_score":0.04054093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07495090810744115,"score_gpt":0.3758619050980312,"score_spread":0.3009109969905901,"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."}}