{"id":"W4390944066","doi":"10.1108/eor-06-2023-0003","title":"Agricultural and food systems in the Mekong region: drivers of transformation and pathways of change","year":2019,"lang":"en","type":"article","venue":"Emerald Open Research","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Higher Education Funding Council for England","keywords":"Livelihood; Food systems; Agriculture; Agrarian society; Consumption (sociology); Food security; Business; Natural resource economics; Economic system; Food processing; Supply chain; Agricultural productivity; Urbanization; Economics; Economic geography; Economic growth; Geography; Marketing; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000862317,0.0000819182,0.0001818741,0.00001897158,0.000098862,0.00007524573,0.0003751712,0.00006469915,0.00001453554],"category_scores_gemma":[0.0000124833,0.00002216514,0.00002187921,0.0004430425,0.00005913059,0.0003432531,0.0001391823,0.0001458117,0.000002820032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001528174,"about_ca_system_score_gemma":0.000005692613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002583527,"about_ca_topic_score_gemma":0.0008330875,"domain_scores_codex":[0.9987725,0.0002449233,0.0002186949,0.0001695606,0.0003892411,0.000205067],"domain_scores_gemma":[0.9995818,0.0001467888,0.00006271469,0.00004710744,0.0001197586,0.0000418923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005324696,0.0007413263,0.3284783,0.00146934,0.0002186777,0.00001797186,0.1159395,0.00001345381,0.1230843,0.2725396,0.01696826,0.1399968],"study_design_scores_gemma":[0.0002811991,0.0004474048,0.9837503,0.0001110076,0.00000236041,0.00001254677,0.01169022,0.00001309926,0.0005252479,0.0004668972,0.002616488,0.00008323761],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941443,0.0003921776,6.87815e-8,0.002413872,0.00002719336,0.001444508,0.00001393451,0.000003597082,0.001560351],"genre_scores_gemma":[0.9993954,0.000304242,0.000006526649,0.00004699795,0.00003297086,0.00006603084,0.00002890745,4.415965e-7,0.0001185106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6552719,"threshold_uncertainty_score":0.3905538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2087122877098511,"score_gpt":0.3043816640444286,"score_spread":0.09566937633457748,"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."}}