{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001278468,0.0003253781,0.0002003379,0.001721075,0.001463672,0.001317953,0.0005174002,0.0002418431,0.001680245],"category_scores_gemma":[0.0009796438,0.0002555548,0.0002759197,0.003287028,0.0006562396,0.0007829115,0.001202094,0.0002733307,0.00007615874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007478701,"about_ca_system_score_gemma":0.01953203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1151997,"about_ca_topic_score_gemma":0.3289963,"domain_scores_codex":[0.999532,0.0001199542,0.00004131153,0.00006223719,0.0001247324,0.000119781],"domain_scores_gemma":[0.9994987,0.00008523308,0.00009155973,0.00005270464,0.0001463244,0.0001254912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008465125,0.0002432582,0.6710114,0.0006044072,0.0001406349,0.0008995837,0.01301472,0.02006114,0.003139235,0.03769898,0.01274231,0.2403597],"study_design_scores_gemma":[0.00003870706,0.0002349425,0.8588751,0.0002152312,0.0001474644,0.0002100387,0.0196773,0.02512347,0.001375661,0.01123414,0.08278956,0.00007841743],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798921,0.0007088694,0.004553155,0.001186524,0.00002097622,0.0002972234,0.0008991655,0.00004815868,0.01239383],"genre_scores_gemma":[0.9836581,0.000546306,0.01066498,0.00009577746,0.000006726051,0.0002168598,0.001270357,0.00001128303,0.003529675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1151997,"threshold_uncertainty_score":0.2290583,"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."}}