{"id":"W6980318051","doi":"","title":"Bulk Handling of Paddy and Rice in Malaysia: an Economic Analysis","year":2017,"lang":"en","type":"article","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Food Drying and Modeling","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut Penyelidikan dan Kemajuan Pertanian Malaysia; Australian Centre for International Agricultural Research; International Development Research Centre","keywords":"Incentive; Postharvest; Economic analysis; Economic impact analysis; Economic feasibility; Product (mathematics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0004027159,0.00006669542,0.0002325289,0.00006365521,0.0002565149,0.00002946622,0.0003396865,0.00006446406,0.0001652066],"category_scores_gemma":[0.00001474515,0.00004187322,0.00007534159,0.0001010642,0.0001998195,0.0003280664,0.0001460529,0.00007966258,0.000006562135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001613094,"about_ca_system_score_gemma":0.000009972121,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03307715,"about_ca_topic_score_gemma":0.03538334,"domain_scores_codex":[0.99937,0.00004933383,0.0000974791,0.0002320281,0.00008677505,0.0001644104],"domain_scores_gemma":[0.9995685,0.00008275999,0.0001126151,0.0001162111,0.00004032191,0.00007957147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002975342,0.0002887225,0.6245866,0.00008857535,0.0004217412,0.00006970413,0.004127848,0.006360755,0.2131512,0.0008225357,0.00005829343,0.1497266],"study_design_scores_gemma":[0.000340834,0.0002215288,0.9519125,0.00002125057,0.00007474117,0.000001412682,0.00449758,0.04163321,0.0009937572,0.00005478032,0.0001144218,0.0001339368],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998859,0.00004415527,0.00001485634,0.0004808283,0.00001522753,0.00005337327,0.00003271874,0.000005225464,0.0004945528],"genre_scores_gemma":[0.9993637,0.0001493255,0.0002438824,0.000005452641,0.00001767139,8.503366e-8,0.00001283021,4.586546e-7,0.000206634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.327326,"threshold_uncertainty_score":0.9822184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04399061847247993,"score_gpt":0.2432954027698438,"score_spread":0.1993047842973639,"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."}}