{"id":"W1916502630","doi":"10.5376/mpb.2011.02.0011","title":"NERICA: A Hope for Fighting Hunger and Poverty in Africa","year":2011,"lang":"en","type":"article","venue":"Molecular Plant Breeding","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Poverty; Biology; Biotechnology; Development economics; Economic growth; Economics","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":[0.000177656,0.00008732169,0.0001000109,0.00001395535,0.0001153718,0.00004925486,0.00008712483,0.00005393284,0.00006712295],"category_scores_gemma":[0.00005479008,0.00003121482,0.00002816475,0.0002649941,0.00001258481,0.0001710439,0.00004364071,0.00007326708,0.000002409489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008259962,"about_ca_system_score_gemma":0.000001506746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001905472,"about_ca_topic_score_gemma":0.0000911893,"domain_scores_codex":[0.99939,0.0000184635,0.0001374311,0.0001816403,0.00007124905,0.0002012344],"domain_scores_gemma":[0.9997129,0.0001287105,0.00007075459,0.00001906886,0.00003296932,0.00003555502],"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":[0.00006206909,0.00005906364,0.006811901,0.00001125228,0.00001792043,0.00003306181,0.0005620351,0.000001003296,0.9535462,0.002698928,0.003951762,0.03224476],"study_design_scores_gemma":[0.001139625,0.00150747,0.6895924,0.0002533375,0.00009701659,0.000259843,0.004727694,0.001433628,0.05754698,0.005076519,0.2367377,0.001627759],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919572,0.0001467854,0.00003760354,0.0009617043,0.00004445203,0.000170542,0.00002897678,0.00002741164,0.006625325],"genre_scores_gemma":[0.998073,0.00001483364,0.00141405,0.0002841456,0.00006934121,0.00002292056,0.00003429157,6.942913e-7,0.00008676671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8959993,"threshold_uncertainty_score":0.1272904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07445290376226844,"score_gpt":0.2182519734675286,"score_spread":0.1437990697052602,"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."}}