{"id":"W2587973607","doi":"10.5539/jas.v9n3p202","title":"Performance of Vegetable Production and Marketing in Peri-Urban Kumasi, Ghana","year":2017,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Kwame Nkrumah University of Science and Technology","keywords":"Business; Production (economics); Investment (military); Leafy vegetables; Margin (machine learning); Distribution (mathematics); Agricultural economics; Gross margin; Agricultural science; Marketing; Economics; Horticulture; Mathematics","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":[0.001844662,0.0001019286,0.0001913598,0.00003172623,0.0007059563,0.0002300283,0.000514449,0.00004131418,0.00003372204],"category_scores_gemma":[0.0008489143,0.00002989752,0.00004155771,0.0005487783,0.0003064972,0.002846104,0.0001124912,0.0001816378,0.000001072768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003975502,"about_ca_system_score_gemma":0.00001919754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000102157,"about_ca_topic_score_gemma":0.0001614386,"domain_scores_codex":[0.9987713,0.00004327125,0.0003982583,0.0001777918,0.0003929633,0.0002164512],"domain_scores_gemma":[0.9982813,0.00008315042,0.0009785898,0.00005765825,0.0005267701,0.00007250629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000347301,0.00004046267,0.2559043,0.00001300057,0.000004089683,0.000001357667,0.0001416697,0.00001489825,0.7290339,0.0000519337,0.000177857,0.01458171],"study_design_scores_gemma":[0.00005992299,0.0001885551,0.9827833,0.0001458357,0.000007536107,0.0001063792,0.0009396877,0.0000234813,0.0151868,0.000007350374,0.0004565048,0.00009467193],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957488,0.0001931895,4.784384e-8,0.002175886,0.0002478576,0.00008808826,0.000001168597,0.000004036407,0.001540982],"genre_scores_gemma":[0.9989618,0.000200716,0.000241861,0.00001191131,0.0002667017,0.000001201153,6.326544e-7,3.006544e-7,0.0003148575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7268789,"threshold_uncertainty_score":0.5429717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02434186995792094,"score_gpt":0.2450166321577044,"score_spread":0.2206747621997835,"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."}}