{"id":"W2383988305","doi":"","title":"Study on Genetic Gains of Yield and Ear Characters of Different Eras Maize Hybrids in North China","year":2011,"lang":"en","type":"article","venue":"Seed","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Heterosis; Hybrid; Yield (engineering); Agronomy; Biology; China; Biotechnology; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005414426,0.0003647738,0.0003071762,0.0009430329,0.0003633697,0.0001819196,0.0002896468,0.0001455239,0.0006505756],"category_scores_gemma":[0.0002302855,0.0002122356,0.0004545379,0.0007010247,0.0002907928,0.000240279,0.0003498616,0.0002306542,0.00008992571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008802678,"about_ca_system_score_gemma":0.0005049815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00625286,"about_ca_topic_score_gemma":0.01632423,"domain_scores_codex":[0.9996732,0.00004491863,0.0000296307,0.0001209569,0.00007920246,0.00005198139],"domain_scores_gemma":[0.9997697,0.00005565839,0.00005121989,0.00003554712,0.0000361066,0.0000516355],"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":[0.0005214429,0.0001091244,0.0410986,0.00007222351,0.000158985,0.0006207744,0.001066529,0.0004856157,0.9388038,0.0003623574,0.00004158501,0.01665894],"study_design_scores_gemma":[0.00003339111,0.0004534031,0.9670511,0.000003961015,0.0001217219,0.0004678909,0.00039508,0.000808829,0.02944743,0.00009755338,0.001097913,0.0000216269],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995812,0.00003567663,0.000109094,0.000005865838,6.888769e-7,0.000003642904,0.00004192311,0.000004533788,0.0002174284],"genre_scores_gemma":[0.9980459,0.0001253066,0.0003944098,0.00001381762,0.000001941109,0.00001415384,0.0002559013,0.000006377616,0.001142231],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00625286,"threshold_uncertainty_score":0.01243293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02891551266935017,"score_gpt":0.2206686468261838,"score_spread":0.1917531341568336,"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."}}