{"id":"W2972991779","doi":"10.1016/j.ecolecon.2019.106447","title":"Metabolic relationships between cities and hinterland: a political-industrial ecology of energy metabolism of Saint-Nazaire metropolitan and port area (France)","year":2019,"lang":"en","type":"article","venue":"Ecological Economics","topic":"Sustainability and Ecological Systems Analysis","field":"Environmental Science","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Agence de l'Environnement et de la Maîtrise de l'Energie; Agence Nationale de la Recherche","keywords":"Urban metabolism; Metropolitan area; Port (circuit theory); Industrial ecology; Political ecology; Politics; Industrial symbiosis; Order (exchange); Material flow analysis; Economic geography; Regional science; Ecology; Sociology; Environmental planning; Environmental resource management; Geography; Business; Urban planning; Political science; Sustainability; Economics; Engineering; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008672159,0.0001915423,0.0009768669,0.00008796481,0.00009757357,0.00001750406,0.0001893772,0.0003843353,0.001866729],"category_scores_gemma":[0.0005193882,0.0001525187,0.0001529456,0.0001405026,0.0007154227,0.0001602368,0.0003223841,0.0002133319,0.00001384557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002916216,"about_ca_system_score_gemma":0.00002585708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002135043,"about_ca_topic_score_gemma":0.0007094063,"domain_scores_codex":[0.9980274,0.0002567825,0.0007564979,0.0004438965,0.00008468746,0.0004306693],"domain_scores_gemma":[0.9983721,0.0008187025,0.0003182713,0.0002403796,0.00002157725,0.0002289427],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001963519,0.00006022847,0.8888656,0.000009776165,0.00008532881,9.213199e-7,0.00004727509,0.000140655,0.00001634775,0.1100161,0.00001882653,0.0007193159],"study_design_scores_gemma":[0.0005523776,0.0002407006,0.9613556,0.000002724192,0.0001115561,0.000004643261,0.001421178,0.0004743683,0.0001119172,0.03135327,0.004200401,0.0001712935],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950877,0.0001146082,0.00002752775,0.000540762,0.00009337718,0.0002260001,0.00004652458,0.0000148481,0.003848684],"genre_scores_gemma":[0.9991497,0.00006557073,0.0001761952,0.0001100422,0.00005809408,0.00001830674,0.00001131368,0.000007870397,0.0004028751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07866281,"threshold_uncertainty_score":0.9990457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0209356353048452,"score_gpt":0.206463687420699,"score_spread":0.1855280521158539,"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."}}