{"id":"W2352746151","doi":"","title":"Characteristics of Indica TGMS Line 2301 S and the Techniques for Its High-yielding Seed Production","year":2008,"lang":"en","type":"article","venue":"Seed","topic":"Silicon Effects in Agriculture","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Biology; Horticulture","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":[0.00007488199,0.0002076357,0.0001253755,0.0003861429,0.0001735943,0.0001484674,0.0001779344,0.0001677605,0.002147574],"category_scores_gemma":[0.0001554965,0.0001288199,0.0001618674,0.0003218827,0.0001576327,0.0001218058,0.00009176618,0.0004497557,0.0008256654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000173095,"about_ca_system_score_gemma":0.0001350507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001919316,"about_ca_topic_score_gemma":0.002663843,"domain_scores_codex":[0.9999532,0.000007529732,0.000005396562,0.00001453799,0.00001179938,0.000007625832],"domain_scores_gemma":[0.9997875,0.00007458263,0.00004544658,0.00002236692,0.00002137556,0.00004882161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005991775,0.0000161759,0.0004620877,0.000006348139,0.000001503217,0.00005303597,0.00002174003,0.00003315258,0.9986042,0.00006287039,0.00003068834,0.0006482511],"study_design_scores_gemma":[0.0000332608,0.000701656,0.1327286,0.00000636384,0.00005126079,0.00140197,0.0001455401,0.001313659,0.8559489,0.0002064299,0.007432308,0.0000300445],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867654,0.0002663356,0.006538489,0.0001100305,0.00001070278,0.0000746985,0.002758283,0.0001438519,0.003332325],"genre_scores_gemma":[0.9768664,0.0002076512,0.006720076,0.00009078446,0.00001188367,0.0001216087,0.007158097,0.0001978442,0.00862567],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002147574,"threshold_uncertainty_score":0.007184386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01486839381696663,"score_gpt":0.2135292234122134,"score_spread":0.1986608295952468,"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."}}