{"id":"W3216619694","doi":"10.1016/j.oneear.2021.10.012","title":"Urbanization and agrobiodiversity: Leveraging a key nexus for sustainable development","year":2021,"lang":"en","type":"article","venue":"One Earth","topic":"Urban Agriculture and Sustainability","field":"Agricultural and Biological Sciences","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Socio-Environmental Synthesis Center; Pennsylvania State University; National Science Foundation","keywords":"Agricultural biodiversity; Nexus (standard); Urbanization; Food security; Sustainable development; Environmental planning; Food systems; Geography; Natural resource economics; Business; Environmental resource management; Agriculture; Economic growth; Ecology; Economics; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009182186,0.0003365193,0.0003238636,0.001143301,0.001788325,0.004411189,0.0005735915,0.0009380396,0.005291931],"category_scores_gemma":[0.001049419,0.0001868695,0.0003687019,0.001791411,0.008450624,0.00409026,0.006837992,0.0009496454,0.0002367158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002069448,"about_ca_system_score_gemma":0.003233592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001834871,"about_ca_topic_score_gemma":0.005429999,"domain_scores_codex":[0.9992089,0.0004013247,0.00002901165,0.0001292421,0.0000945551,0.0001369556],"domain_scores_gemma":[0.9992118,0.0002906487,0.0002058766,0.00007352367,0.00006418514,0.0001539989],"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":[0.00002474415,0.00006011386,0.02322045,0.0001866103,0.00003112014,0.0007412725,0.005626245,0.002524116,0.001600749,0.9356656,0.0005369824,0.02978197],"study_design_scores_gemma":[0.00001237896,0.0001378142,0.05208405,0.0004411289,0.00006772899,0.0009086045,0.03687653,0.005923215,0.001458427,0.8297968,0.07224265,0.00005078001],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5892634,0.005302113,0.09224359,0.02120597,0.0001221415,0.0002363756,0.0002324458,0.00009423614,0.2912996],"genre_scores_gemma":[0.9903684,0.001423153,0.006329269,0.0001978657,0.00001743904,0.00004496256,0.00002932354,0.00000817572,0.00158149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005291931,"threshold_uncertainty_score":0.01770329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01719993618390449,"score_gpt":0.1714449738519133,"score_spread":0.1542450376680088,"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."}}