{"id":"W1434924751","doi":"","title":"组织培养、分子标记和QT L技术在青花菜育种中的应用","year":2015,"lang":"zh","type":"article","venue":"分子植物育种","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000343293,0.0003040295,0.0003203283,0.0001389827,0.00007817741,0.00003669915,0.0003855619,0.0004896443,0.0002962841],"category_scores_gemma":[0.0001242895,0.0003201987,0.00009718706,0.0002838096,0.0001673419,0.0002187044,0.00008915242,0.0005522501,0.002299979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009313745,"about_ca_system_score_gemma":0.00009378188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001229932,"about_ca_topic_score_gemma":0.00009420233,"domain_scores_codex":[0.9985857,0.00005495503,0.0003093675,0.0003072978,0.0002059117,0.0005367748],"domain_scores_gemma":[0.9990264,0.00004374075,0.0000461909,0.0006058715,0.00006520026,0.0002125892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002667458,0.00009844599,0.003789838,0.000180647,0.0002233586,0.0002317641,0.00212102,0.003735005,0.0003459768,0.9087023,0.06581964,0.01472539],"study_design_scores_gemma":[0.002028106,0.0004923081,0.01003988,0.0001838524,0.0001621207,0.0001425838,0.004990129,0.007700189,0.0006451733,0.8901243,0.08204357,0.001447768],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03193068,0.0159824,0.001001212,0.0007625044,0.001777501,0.0001636312,0.00002973452,0.000986081,0.9473662],"genre_scores_gemma":[0.9936682,0.0002995307,0.0009630529,0.00006831561,0.000370806,0.00001499196,0.00001621509,0.00004657296,0.004552313],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9617375,"threshold_uncertainty_score":0.999925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02289830488710448,"score_gpt":0.220949255149065,"score_spread":0.1980509502619606,"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."}}