{"id":"W1028930797","doi":"","title":"黄瓜序列特征性扩增区域标记（SCAR）的开发","year":2007,"lang":"zh","type":"article","venue":"分子植物育种","topic":"Molecular Biology Techniques and Applications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001240443,0.0005562479,0.0005956591,0.001226178,0.001219394,0.003039544,0.0007270066,0.001043796,0.007729333],"category_scores_gemma":[0.001770642,0.0006411762,0.0005247907,0.001089102,0.001971162,0.002463176,0.0007448849,0.001386637,0.003679021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001055889,"about_ca_system_score_gemma":0.001403819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001190141,"about_ca_topic_score_gemma":0.001199872,"domain_scores_codex":[0.9986922,0.0002001403,0.0001007981,0.0003568413,0.0005302481,0.0001197538],"domain_scores_gemma":[0.9989647,0.0003393208,0.0001130563,0.00009891394,0.0004088647,0.00007531567],"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":[0.0002966023,0.0001641904,0.01210781,0.001116125,0.0001059145,0.001701182,0.005447367,0.003917965,0.4597315,0.1254143,0.008213924,0.3817831],"study_design_scores_gemma":[0.0001044884,0.0005560525,0.02169792,0.0003034474,0.0002723207,0.005984848,0.007746066,0.01399375,0.62679,0.08652595,0.2357867,0.000238344],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3331819,0.004080977,0.4361264,0.002474306,0.0008217877,0.0006401578,0.001191408,0.00237463,0.2191084],"genre_scores_gemma":[0.690164,0.001863571,0.2247238,0.0008190781,0.0001310147,0.0004918524,0.001033088,0.0003746401,0.08039905],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007729333,"threshold_uncertainty_score":0.02585715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007071596467745489,"score_gpt":0.2835917888107073,"score_spread":0.2765201923429618,"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."}}