{"id":"W4376133730","doi":"10.1038/s41597-023-02163-6","title":"A spatio-temporal dataset on food flows for four West African cities","year":2023,"lang":"en","type":"article","venue":"Scientific Data","topic":"Urban Agriculture and Sustainability","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Bundesministerium für Bildung und Forschung; Consortium of International Agricultural Research Centers; Deutsche Forschungsgemeinschaft","keywords":"Food security; Geography; Sustainability; Psychological intervention; Resilience (materials science); Socioeconomics; Environmental planning; Business; Agriculture; Ecology; Economics","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":[0.000718602,0.0005974441,0.0004818306,0.004261724,0.0006379624,0.0008572592,0.0006533633,0.0008190852,0.003300866],"category_scores_gemma":[0.002993572,0.0002965734,0.0005097477,0.009362658,0.0002559613,0.0006811519,0.0009481627,0.0006618258,0.001722268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001184902,"about_ca_system_score_gemma":0.001646691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09551372,"about_ca_topic_score_gemma":0.1078963,"domain_scores_codex":[0.9995261,0.0000917731,0.00008077026,0.00009960394,0.0001028534,0.0000988784],"domain_scores_gemma":[0.9984738,0.0004077941,0.0003576756,0.0002100115,0.0004004134,0.0001502288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00103509,0.0006696444,0.5449519,0.003375023,0.0005077855,0.002022885,0.004315959,0.02315575,0.005580777,0.00485208,0.3369663,0.07256672],"study_design_scores_gemma":[0.0001669813,0.0001010798,0.7032374,0.0007454798,0.00009537757,0.0004044154,0.007463723,0.01311578,0.002620744,0.001360727,0.2705764,0.0001121031],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1224945,0.0003139741,0.0006775488,0.0003045018,0.00002951086,0.0001256879,0.8740605,0.0001836622,0.0018101],"genre_scores_gemma":[0.1081624,0.0003645733,0.004281894,0.00005827334,0.00001690938,0.0005473885,0.8853145,0.00003309673,0.001221005],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09551372,"threshold_uncertainty_score":0.1899155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1062985569765529,"score_gpt":0.2652192563099462,"score_spread":0.1589206993333933,"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."}}