{"id":"W4411048287","doi":"10.1016/j.ige.2025.06.001","title":"Urban geological information platform for smart city construction: A shift from public service to integration with urban engineering","year":2025,"lang":"en","type":"article","venue":"Intelligent geoengineering.","topic":"Geological Modeling and Analysis","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"China Geological Survey; China University of Geosciences, Wuhan; Ministry of Natural Resources","keywords":"Smart city; Service (business); Architectural engineering; Construction engineering; Public service; Civil engineering; Transport engineering; Environmental planning; Engineering; Computer science; Geography; Business; World Wide Web; Internet of Things; Political science; Public administration","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001084839,0.000328966,0.0002665633,0.0007468747,0.0005229483,0.00247656,0.001411181,0.0005822637,0.001933339],"category_scores_gemma":[0.001117764,0.0001965699,0.0003090992,0.001282299,0.0007419661,0.003462068,0.004166541,0.0008671609,0.0007207463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009676163,"about_ca_system_score_gemma":0.002112602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005949865,"about_ca_topic_score_gemma":0.005137717,"domain_scores_codex":[0.9994592,0.0001082505,0.00003472726,0.0001014251,0.0001945079,0.0001019242],"domain_scores_gemma":[0.9991583,0.00007868147,0.00004633918,0.0003101333,0.000205646,0.0002008771],"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":[0.0005944769,0.0006141109,0.05066516,0.0003668535,0.0001207114,0.00187154,0.00385251,0.07487287,0.06173965,0.3116046,0.03929739,0.4544001],"study_design_scores_gemma":[0.0001421148,0.0005172582,0.02317892,0.0001771679,0.0001484368,0.0007618957,0.003915391,0.6007739,0.04048249,0.0663413,0.2634123,0.0001488212],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.482077,0.0005796264,0.4703988,0.005382565,0.000325787,0.0003850691,0.001020501,0.006873285,0.03295738],"genre_scores_gemma":[0.8695406,0.0002720383,0.1240045,0.0002441442,0.00007145595,0.0001052457,0.001428507,0.0001808988,0.004152565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005949865,"threshold_uncertainty_score":0.01183045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01820480769358097,"score_gpt":0.1977419944253561,"score_spread":0.1795371867317752,"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."}}