{"id":"W6920268178","doi":"10.60692/2556y-7n583","title":"A spatio-temporal dataset on food flows for four West African cities","year":2023,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Urban Agriculture and Sustainability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Food security; Resilience (materials science); Food supply; Food systems; Food policy; Food processing; Urbanization; Pandemic","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":[0.0007605804,0.0005310486,0.0004094092,0.004388432,0.0006418723,0.0008658399,0.0005250211,0.0006580214,0.003272597],"category_scores_gemma":[0.003183012,0.0002643991,0.0004019162,0.009751761,0.0002387103,0.0006681246,0.0009211035,0.0005248439,0.001328342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001203814,"about_ca_system_score_gemma":0.001601589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1074704,"about_ca_topic_score_gemma":0.107037,"domain_scores_codex":[0.9995301,0.00009875138,0.00007681383,0.00009718294,0.00009737368,0.00009982904],"domain_scores_gemma":[0.9984249,0.0004656751,0.0003461178,0.0002263814,0.0003918564,0.000145194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009236107,0.0005585056,0.6820982,0.002459708,0.000413279,0.001686483,0.004411074,0.02285252,0.004992761,0.004273487,0.2021347,0.07319582],"study_design_scores_gemma":[0.00012272,0.00008729031,0.8144357,0.0005298802,0.00007631588,0.0002782952,0.007874486,0.01557424,0.0024352,0.0009806656,0.1575198,0.00008554378],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2538933,0.0002962138,0.000706365,0.0003473962,0.00002697425,0.0001523838,0.7421541,0.0002032638,0.002220069],"genre_scores_gemma":[0.2226927,0.0004015126,0.004920413,0.00005839809,0.0000176709,0.0005962132,0.7697634,0.00003700952,0.001512656],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1074704,"threshold_uncertainty_score":0.2136897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05659894281200762,"score_gpt":0.2044978755950829,"score_spread":0.1478989327830753,"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."}}