{"id":"W2907544000","doi":"10.2495/dne-v13-n4-349-360","title":"Urban foodprints (UF) – Establishing baseline scenarios for the sustainability assessment of high-yield urban agriculture","year":2018,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Urban Agriculture and Sustainability","field":"Agricultural and Biological Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"King Abdulaziz City for Science and Technology","keywords":"Baseline (sea); Sustainability; Agriculture; Yield (engineering); Environmental science; Urban sustainability; Urban agriculture; Environmental resource management; Environmental planning; Geography; Political science; Ecology; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001606115,0.0001943979,0.000300574,0.00003825856,0.0002153178,0.0001641413,0.000735243,0.000275557,0.00004248648],"category_scores_gemma":[0.00123544,0.00006487613,0.0002156038,0.0002542463,0.0001464886,0.0003562536,0.000115328,0.0005543514,2.14717e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002054303,"about_ca_system_score_gemma":0.00009761251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001196816,"about_ca_topic_score_gemma":0.0004587684,"domain_scores_codex":[0.9983071,0.0001326148,0.0005656573,0.000248745,0.0004992418,0.0002466037],"domain_scores_gemma":[0.9943335,0.001645406,0.0005358594,0.00008655064,0.00329528,0.0001033708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004995762,0.004030102,0.3565474,0.0003547987,0.003540435,0.000153211,0.004187898,0.003937039,0.07708178,0.05784987,0.2484575,0.2388643],"study_design_scores_gemma":[0.002131549,0.004645303,0.8166483,0.0002895564,0.0005311572,0.0002981382,0.007241322,0.02123138,0.003094346,0.02706631,0.1158251,0.0009975844],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9587056,0.001249097,0.02159966,0.01567324,0.001575248,0.0008885567,0.0001582264,0.00002407939,0.0001262957],"genre_scores_gemma":[0.9961942,0.0000995454,0.001588988,0.000378843,0.001511102,0.000008472522,0.00003132015,0.000001963592,0.0001855307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4601009,"threshold_uncertainty_score":0.2645572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01227353916270991,"score_gpt":0.2539018045099304,"score_spread":0.2416282653472205,"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."}}