{"id":"W4400677454","doi":"10.1016/j.eja.2024.127281","title":"High yield, good eating quality, and high N use efficiency for medium hybrid indica rice: From the perspective of balanced source-sink relationships at heading","year":2024,"lang":"en","type":"article","venue":"European Journal of Agronomy","topic":"Rice Cultivation and Yield Improvement","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Agriculture","funders":"National Key Research and Development Program of China; Anhui Agricultural University","keywords":"Sink (geography); Agronomy; Heading (navigation); Yield (engineering); Perspective (graphical); Environmental science; Mathematics; Agricultural engineering; Biology; Materials science; Engineering; Geography","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":[0.00106825,0.00009770789,0.0001576027,0.00001836999,0.0002806684,0.0001220932,0.0001763685,0.00001725296,0.00008329756],"category_scores_gemma":[0.0004805735,0.00003587767,0.00009544982,0.0001334607,0.00007418232,0.0001906683,0.00007491815,0.000204228,0.000004720415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005170479,"about_ca_system_score_gemma":0.00001389782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001541719,"about_ca_topic_score_gemma":0.00001939861,"domain_scores_codex":[0.9988296,0.0002677973,0.0004422413,0.0001617881,0.000172279,0.00012628],"domain_scores_gemma":[0.9977392,0.001695792,0.0003383211,0.00004278836,0.0001176275,0.00006626483],"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":[0.0004480478,0.0003711889,0.08658548,0.00009372774,0.000617076,0.00003596781,0.02561181,0.0003317097,0.7644872,0.01432599,0.01464523,0.09244654],"study_design_scores_gemma":[0.0004345779,0.0004865672,0.976948,0.0003302074,0.00005662745,0.00001235088,0.00815508,0.00006884861,0.005722899,0.0006336697,0.006984988,0.0001661472],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907017,0.0004836399,0.001152594,0.00689987,0.0001879128,0.0001538881,0.00003297719,0.00001376877,0.0003736112],"genre_scores_gemma":[0.9983824,0.00003218224,0.0007060501,0.0001673845,0.0004314308,0.000001312232,0.00001149882,0.000002161766,0.0002656176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8903626,"threshold_uncertainty_score":0.2158702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06518688884495319,"score_gpt":0.2594459594591204,"score_spread":0.1942590706141672,"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."}}