{"id":"W1982627164","doi":"10.1038/nature11420","title":"Closing yield gaps through nutrient and water management","year":2012,"lang":"en","type":"article","venue":"Nature","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":2797,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Yield gap; Food security; Agriculture; Sustainability; Nutrient management; Yield (engineering); Natural resource economics; Agricultural productivity; Environmental science; Population; Crop yield; Agricultural economics; Sustainable agriculture; Production (economics); Business; Agronomy; Ecology; Economics; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001304766,0.0002567701,0.0002721995,0.0006041883,0.0008300289,0.001698817,0.000873631,0.000689604,0.005866684],"category_scores_gemma":[0.002537698,0.00010562,0.0002870612,0.00098304,0.0008320537,0.002644432,0.001915651,0.0006402233,0.0004804293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00136897,"about_ca_system_score_gemma":0.003577237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006077931,"about_ca_topic_score_gemma":0.01824079,"domain_scores_codex":[0.9996306,0.00007464691,0.00002816985,0.00007128724,0.0001102335,0.00008514829],"domain_scores_gemma":[0.9989645,0.0002045961,0.00029073,0.0001098544,0.0002493635,0.000180954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000635055,0.001133037,0.04834999,0.0005606431,0.0002230065,0.0004039416,0.001318545,0.0420206,0.03641374,0.1468245,0.02714287,0.6949741],"study_design_scores_gemma":[0.0001433307,0.0005784017,0.1172074,0.0003892426,0.0002891812,0.0002828957,0.006496782,0.05975544,0.01575853,0.5052134,0.2937897,0.00009583023],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6779504,0.007403068,0.1129924,0.03617128,0.00127733,0.0001411384,0.001190917,0.001045871,0.1618276],"genre_scores_gemma":[0.9712352,0.002730006,0.01413551,0.001174329,0.000209604,0.00005391836,0.0002189405,0.00009869796,0.0101439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006077931,"threshold_uncertainty_score":0.01962596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03133668417439492,"score_gpt":0.2552492259529614,"score_spread":0.2239125417785665,"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."}}