{"id":"W4383905100","doi":"10.12688/openreseurope.16054.1","title":"ediblecity: an R package to model and estimate the benefits of urban agriculture","year":2023,"lang":"en","type":"article","venue":"Open Research Europe","topic":"Urban Agriculture and Sustainability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Departament d'Empresa i Coneixement, Generalitat de Catalunya; Horizon 2020 Framework Programme; Ministerio para la Transición Ecológica y el Reto Demográfico; European Commission; Fundación Biodiversidad; Centres de Recerca de Catalunya; Canadian Institute for Advanced Research","keywords":"Urban agriculture; Agriculture; R package; Per capita; Food security; Software package; Implementation; Geography; Business; Agricultural economics; Agricultural science; Environmental science; Agricultural engineering; Computer science; Software; Mathematics; Engineering; Economics; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002628428,0.002253818,0.00128119,0.001561053,0.0004343936,0.00205364,0.002523308,0.001181373,0.04409293],"category_scores_gemma":[0.02022165,0.001271398,0.002688303,0.001684984,0.0005881983,0.001648075,0.002365273,0.002118242,0.02974834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006527661,"about_ca_system_score_gemma":0.002321431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00906925,"about_ca_topic_score_gemma":0.01073105,"domain_scores_codex":[0.9987085,0.0005444346,0.0001122702,0.0002427513,0.0002810009,0.0001111376],"domain_scores_gemma":[0.9923907,0.005727615,0.0004515433,0.0006044227,0.000674524,0.0001511918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000352455,0.0001054632,0.01551917,0.003104543,0.001494313,0.0005637078,0.0004343767,0.09316962,0.002025494,0.01990355,0.7885447,0.07478277],"study_design_scores_gemma":[0.0006377543,0.0001954818,0.01184846,0.0007697071,0.000646118,0.0005880475,0.0001978005,0.1837965,0.005334903,0.05861951,0.7370788,0.0002869371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01373315,0.001638856,0.4036188,0.001866535,0.0006256913,0.0005632706,0.2937177,0.267495,0.01674103],"genre_scores_gemma":[0.1177075,0.002289639,0.4475861,0.002696398,0.0003218031,0.00449499,0.2470366,0.1597866,0.01808044],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04409293,"threshold_uncertainty_score":0.1475055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1215517721427423,"score_gpt":0.3612744715345661,"score_spread":0.2397226993918238,"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."}}