{"id":"W2375350357","doi":"","title":"Study on combined N, P, K, organic fertilization on rice yield and component factors","year":2005,"lang":"en","type":"article","venue":"Dongbei Nongye Daxue xuebao","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Potash; Fertilizer; Yield (engineering); Human fertilization; Agronomy; Organic fertilizer; Potassium; Phosphate; Phosphate fertilizer; Mathematics; Chemistry; Biology; Materials science","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":[0.0003920165,0.0006211433,0.0007189247,0.0002114325,0.000174266,0.0002980877,0.0002076282,0.0002277487,0.0007336379],"category_scores_gemma":[0.0006581054,0.0002274616,0.0005124633,0.0004082073,0.0002304643,0.0002825325,0.0003024335,0.0002730362,0.0001295379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003736269,"about_ca_system_score_gemma":0.0006559023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003593664,"about_ca_topic_score_gemma":0.004867688,"domain_scores_codex":[0.9996417,0.00006715283,0.00002201545,0.0001181765,0.0001029731,0.00004796584],"domain_scores_gemma":[0.9995669,0.000209651,0.00007233987,0.00002429855,0.00006886759,0.00005800306],"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":[0.003321738,0.0004430462,0.0412748,0.0005153753,0.000457363,0.0003765252,0.0001252451,0.006738138,0.920063,0.0002108766,0.0001223852,0.02635143],"study_design_scores_gemma":[0.0003636247,0.007981597,0.4653919,0.00003127904,0.001593384,0.0004299569,0.0003788573,0.04981279,0.4697785,0.0006090942,0.003549725,0.00007923652],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967619,0.0003703136,0.00220304,0.00002338881,0.000008432773,0.00001395185,0.00007492539,0.0000264172,0.000517651],"genre_scores_gemma":[0.9963589,0.0003459477,0.002239116,0.00002605878,0.000006279196,0.00002554662,0.00009653688,0.00001074902,0.0008907761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003593664,"threshold_uncertainty_score":0.007145464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0202948005409829,"score_gpt":0.2430629512152009,"score_spread":0.222768150674218,"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."}}