{"id":"W4377021461","doi":"10.21203/rs.3.rs-2839015/v1","title":"Productivity of Different Nutrient Management Systems under Diverse Rice-Based Crop Rotations in the Dry Zone of Sri Lanka","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Agronomic Practices and Intercropping Systems","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Cropping system; Agronomy; Nutrient management; Intercropping; Productivity; Cropping; Crop rotation; Environmental science; Nutrient; Crop yield; Biomass (ecology); Crop; Agricultural diversification; Mathematics; Agriculture; Biology; Ecology; Economics","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":[0.002382505,0.0001679983,0.0003617728,0.0001047035,0.0001471222,0.0001053397,0.0007628116,0.0001303824,0.00003352909],"category_scores_gemma":[0.0001074807,0.00005954357,0.000156035,0.00052565,0.0001493535,0.00006161101,0.0006876017,0.0005721343,0.00002248951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001871711,"about_ca_system_score_gemma":0.00003302462,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01180932,"about_ca_topic_score_gemma":0.001421675,"domain_scores_codex":[0.9966062,0.001201707,0.0004738837,0.0004708769,0.0009034928,0.0003438727],"domain_scores_gemma":[0.9982367,0.0008368079,0.000304081,0.0003060758,0.0002653688,0.00005103605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004078208,0.03439596,0.4159727,0.08846049,0.003895278,0.0004543784,0.06289752,0.08543673,0.138753,0.07681207,0.02836642,0.06047723],"study_design_scores_gemma":[0.0006056008,0.0008919233,0.8749563,0.00413438,0.00006846154,0.000001266535,0.1088552,0.003669789,0.0009852097,0.0009612353,0.004422359,0.0004483242],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945318,0.0002536653,0.00006344407,0.00184441,0.0003071833,0.002139997,0.0002123461,0.00002433708,0.0006228498],"genre_scores_gemma":[0.9987482,0.0001525498,0.00001141768,0.000005792834,0.0001715215,0.0003806353,0.0001393458,0.00000188255,0.0003886459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4589836,"threshold_uncertainty_score":0.9947711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1479683633679844,"score_gpt":0.3576741894661548,"score_spread":0.2097058260981703,"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."}}