{"id":"W3206567966","doi":"10.3390/land10101090","title":"Comprehensive Food System Planning for Urban Food Security in Nanjing, China","year":2021,"lang":"en","type":"article","venue":"Land","topic":"Urban Agriculture and Sustainability","field":"Agricultural and Biological Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Balsillie School of International Affairs","funders":"Social Sciences and Humanities Research Council of Canada; International Development Research Centre","keywords":"Food security; China; Business; Environmental planning; Food insecurity; Food systems; Urban planning; Economic shortage; Economic growth; Geography; Environmental resource management; Economics; Agriculture; Government (linguistics); Engineering; Civil engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0000889564,0.0001149895,0.0002088763,0.000005547467,0.0001312855,0.00005333043,0.000105404,0.00009490152,0.00001509746],"category_scores_gemma":[0.00003045388,0.00004160524,0.00008652246,0.0002180793,0.00001664371,0.00005942971,0.00004930295,0.0001046725,0.000001636031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004755016,"about_ca_system_score_gemma":0.000008511076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001526174,"about_ca_topic_score_gemma":0.002759326,"domain_scores_codex":[0.9991352,0.00005713379,0.0001655387,0.0002794219,0.00009905396,0.000263651],"domain_scores_gemma":[0.9996092,0.0001385161,0.00004552143,0.00005011499,0.00009441454,0.00006218928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008476377,0.000194182,0.9863807,0.0002923452,0.00004658243,0.0000453201,0.002006554,0.00001946995,0.004280239,0.002939209,0.002555538,0.001155113],"study_design_scores_gemma":[0.0004970555,0.0006908174,0.9429357,0.00007335001,0.00001297672,0.00002205339,0.004873939,0.00009088179,0.000843916,0.002347948,0.04736602,0.0002453398],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970355,0.001263919,0.000003715497,0.0003407976,0.0001062877,0.0002810041,0.00008286184,0.00005366703,0.0008322188],"genre_scores_gemma":[0.9993727,0.000002360651,0.00002384522,0.00007351406,0.0002375763,0.00002849562,0.0001046149,6.790797e-7,0.0001562796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04481049,"threshold_uncertainty_score":0.1696612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01675599699083482,"score_gpt":0.211255935870744,"score_spread":0.1944999388799092,"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."}}