{"id":"W7095138469","doi":"","title":"The mungbean transformation: Diversifying crops, defeating malnutrition. Subramanyan","year":2009,"lang":"en","type":"article","venue":"","topic":"Numerical methods in engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Principal (computer security); Work (physics); International development; Agriculture; Private sector; International comparisons","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003426394,0.0001596752,0.0001151183,0.0003100123,0.001150096,0.0008851325,0.000243192,0.0003567818,0.003089869],"category_scores_gemma":[0.0003353995,0.00006179086,0.00007957718,0.0002874572,0.0005904484,0.0006672229,0.0009902224,0.0006693514,0.0002251064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001469029,"about_ca_system_score_gemma":0.001915149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0225984,"about_ca_topic_score_gemma":0.07944496,"domain_scores_codex":[0.9999186,0.00002953364,0.000001214465,0.000009156111,0.00001335754,0.0000281459],"domain_scores_gemma":[0.9999328,0.00001432461,0.000007472536,0.000002995045,0.00001385821,0.00002860705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007365893,0.0003557649,0.01173575,0.000412852,0.00005401157,0.001538314,0.00385049,0.00479855,0.02517374,0.1493738,0.08363515,0.718335],"study_design_scores_gemma":[0.0001243229,0.0006218319,0.04103255,0.0005897967,0.000118405,0.0008613801,0.02162329,0.01223101,0.01670356,0.1058843,0.8001242,0.00008537143],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6533515,0.02016179,0.01229554,0.08715455,0.00121339,0.0001666391,0.0001183931,0.0001887676,0.2253494],"genre_scores_gemma":[0.8871881,0.008265534,0.01155004,0.003463617,0.00005447535,0.00003875611,0.00004858723,0.0000372753,0.08935368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0225984,"threshold_uncertainty_score":0.04493368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008426444808061156,"score_gpt":0.220601022449085,"score_spread":0.2121745776410238,"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."}}