{"id":"W4206218989","doi":"10.1007/s10708-021-10554-8","title":"City-region or city? That is the question: modelling sprawl in Isfahan using geospatial data and technology","year":2022,"lang":"en","type":"article","venue":"GeoJournal","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"H2020 Marie Skłodowska-Curie Actions","keywords":"Urban sprawl; Metropolitan area; Geography; Geospatial analysis; Economic geography; Land use; Compact city; Urban planning; Environmental planning; Physical geography; Regional science; Cartography; Civil engineering","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":[0.0005766805,0.00008559302,0.0001082693,0.00005873398,0.0005987604,0.00005766292,0.000507518,0.00004337551,0.001210159],"category_scores_gemma":[0.000004861738,0.00005501982,0.00001328155,0.0002887473,0.00003184391,0.0003347049,0.001038191,0.0002973934,0.000008045261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008308472,"about_ca_system_score_gemma":0.00001636118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002394277,"about_ca_topic_score_gemma":0.0036616,"domain_scores_codex":[0.9990549,0.00007668194,0.0001618251,0.000245284,0.0002399726,0.0002213197],"domain_scores_gemma":[0.9995114,0.00002265519,0.0001037195,0.0003192665,0.000003481926,0.00003951041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006531576,0.00005200554,0.9207543,0.0000112545,0.00001975891,0.0001186397,0.0009669412,0.07251199,0.00009564101,0.00002093153,0.0004194358,0.004963785],"study_design_scores_gemma":[0.0004483926,0.00006567948,0.006751084,0.00004606803,0.00003342052,0.001107659,0.001262002,0.9760076,0.00009865705,0.002234766,0.01175832,0.000186303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926958,0.0002073569,0.002686573,0.004059889,0.0001359151,0.0001003635,0.00001349573,0.00001455173,0.00008603845],"genre_scores_gemma":[0.9990786,0.0001336894,0.0003580083,0.0003038868,0.00007181315,0.000004600392,0.000004450337,0.000006519057,0.00003837381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9140032,"threshold_uncertainty_score":0.9997029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06732537271953448,"score_gpt":0.274389371455378,"score_spread":0.2070639987358435,"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."}}