{"id":"W1496019296","doi":"","title":"梅花品种“美人”叶片离体再生体系建立","year":2006,"lang":"zh","type":"article","venue":"分子植物育种","topic":"Plant tissue culture and regeneration","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0001101491,0.000236781,0.0001765194,0.00003076168,0.0001618045,0.00006352618,0.0001712017,0.0003987059,0.00007459347],"category_scores_gemma":[0.00001631528,0.0002114208,0.0001289471,0.00008551841,0.00008032672,0.000004784485,0.00006551782,0.0001140726,0.0003441382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002210603,"about_ca_system_score_gemma":0.0001242235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005900317,"about_ca_topic_score_gemma":0.002060465,"domain_scores_codex":[0.9987935,0.0000690144,0.0002503909,0.0004164481,0.0001407019,0.0003299727],"domain_scores_gemma":[0.9994196,0.000005581059,0.00009473272,0.0003253636,0.00007715286,0.0000775994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001780099,0.0001136814,0.001033299,0.00002750892,0.00005087439,0.00002407563,0.00002751079,0.0001034634,0.7820863,0.002115096,0.2116538,0.002746546],"study_design_scores_gemma":[0.0004519752,0.0001237118,0.00194061,0.00002236898,0.0000587569,0.00006590581,0.00002387901,0.00003923341,0.2395868,0.0003265268,0.7570198,0.0003405009],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3748068,0.1038251,0.002713882,0.004121667,0.00327474,0.000700755,0.0003628353,0.00009426587,0.5101],"genre_scores_gemma":[0.9174918,0.0005800723,0.0002548326,0.0002368572,0.005611883,0.00001046963,0.001412067,0.00002779901,0.07437421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5453659,"threshold_uncertainty_score":0.8621489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006319459818569936,"score_gpt":0.2139977888753019,"score_spread":0.207678329056732,"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."}}