{"id":"W2998785950","doi":"10.5539/jas.v12n2p106","title":"Technical Efficiency of Farms, and Fight Against Poverty: Case of the Cashew Sector in Côte d’Ivoire","year":2020,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Data envelopment analysis; Agricultural economics; Poverty; Agricultural science; Hectare; Food security; Business; Scale (ratio); Subsistence agriculture; Economics; Geography; Economic growth; Mathematics; Statistics; Environmental 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001401952,0.0002780474,0.0002721868,0.001562024,0.0009628655,0.001264081,0.000423749,0.0005812467,0.001439186],"category_scores_gemma":[0.001788859,0.000174659,0.0003825586,0.001631851,0.000947077,0.0008656667,0.001042644,0.0003421682,0.00008876954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003249189,"about_ca_system_score_gemma":0.001815733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06317624,"about_ca_topic_score_gemma":0.07143547,"domain_scores_codex":[0.9990783,0.0003609593,0.00002649506,0.00005826615,0.0000905417,0.000385526],"domain_scores_gemma":[0.9988028,0.0004928394,0.0003110485,0.00003906402,0.0001722355,0.0001820182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000234848,0.0003964673,0.9231246,0.0002344828,0.0001590574,0.0194348,0.01643894,0.005681377,0.00212533,0.007792727,0.0008021579,0.02357521],"study_design_scores_gemma":[0.00001279766,0.0001988067,0.933002,0.0001820218,0.00004787646,0.001180785,0.05785187,0.003521045,0.0003100092,0.0008344528,0.002840337,0.00001806676],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983322,0.0002550145,0.00007205928,0.0001691872,0.000001314426,0.000005767164,0.00001587238,5.34418e-7,0.00114804],"genre_scores_gemma":[0.9993812,0.0002104049,0.00005757497,0.00001415422,0.000001590123,0.000002950384,0.00001248176,3.983654e-7,0.0003193143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06317624,"threshold_uncertainty_score":0.125617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03803062954217432,"score_gpt":0.3132947230354873,"score_spread":0.275264093493313,"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."}}