{"id":"W3018799276","doi":"10.3390/admsci10020026","title":"The Dynamics between State Control and Metropolitan Governance Capacity","year":2020,"lang":"en","type":"article","venue":"Administrative Sciences","topic":"Public Policy and Administration Research","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Decentralization; Corporate governance; State (computer science); Control (management); Politics; Government (linguistics); Mandate; Public administration; Local government; Business; Political science; Economics; Geography; Management; Finance; Computer 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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.001753561,0.0001041539,0.0001452177,0.00001691834,0.002780409,0.0006682711,0.0006116307,0.00004194009,0.00003168812],"category_scores_gemma":[0.002301994,0.00007350338,0.00003899333,0.0006139643,0.005764295,0.0004665896,0.00004480107,0.000195919,0.00001268493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001109139,"about_ca_system_score_gemma":0.0009495317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001457177,"about_ca_topic_score_gemma":0.008688295,"domain_scores_codex":[0.9977715,0.0004542107,0.0002117783,0.0003055857,0.000746589,0.0005103443],"domain_scores_gemma":[0.9980515,0.00124157,0.0001412807,0.00008830201,0.0001023803,0.0003750146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001184385,0.000008571441,0.0179662,0.000002736339,0.00001607686,0.000002057827,0.002695677,5.291562e-7,0.00001895227,0.9731062,0.0006905839,0.00548055],"study_design_scores_gemma":[0.001905263,0.003431836,0.2649832,0.00004413783,0.00005441194,0.000005608026,0.1501084,0.01033839,0.001264695,0.1189695,0.4475979,0.001296673],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4226301,0.000232883,0.001147004,0.3901412,0.0001276507,0.0004986131,0.0004982502,0.0000846992,0.1846396],"genre_scores_gemma":[0.9973197,0.0001358827,0.0001665037,0.0008784937,0.0001861061,0.00001136747,0.000001212463,0.000003112035,0.001297596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8541368,"threshold_uncertainty_score":0.9985178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1320253717452167,"score_gpt":0.4146244559003749,"score_spread":0.2825990841551582,"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."}}