{"id":"W375241660","doi":"","title":"Microarray-assisted Marker Development for Molecular Breeding","year":2007,"lang":"en","type":"article","venue":"分子植物育种","topic":"Animal Genetics and Reproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Molecular marker; Biology; Computational biology; Genetics; Gene","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":[0.0004205212,0.0001094579,0.00007775497,0.00003394515,0.00009202326,0.00001491688,0.00009179342,0.0001132239,0.000007837893],"category_scores_gemma":[0.00003488662,0.0001050672,0.00006811913,0.00005564743,0.00003057199,0.000001157525,0.00005163498,0.00003774617,0.000007350782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000154987,"about_ca_system_score_gemma":0.00004224405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002463654,"about_ca_topic_score_gemma":0.0000104059,"domain_scores_codex":[0.9991558,0.000008986612,0.0001766999,0.0003308384,0.00008142483,0.0002462037],"domain_scores_gemma":[0.9996029,0.000004000538,0.00005158853,0.0001818254,0.00009631523,0.00006343841],"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":[0.00006263308,0.00003202308,0.000878112,0.00001351264,0.00003896367,0.000001730776,0.00002198785,0.00000482775,0.9709942,0.00005293766,0.001222565,0.02667655],"study_design_scores_gemma":[0.0002526022,0.0001010192,0.0181221,0.000005356551,0.000009058003,0.00001583014,0.00004044049,0.000003906237,0.7340832,0.00002656651,0.2472013,0.0001385962],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8914203,0.0008862718,0.1031979,0.0001218722,0.0003006521,0.0002368931,0.000002800317,0.00001513606,0.003818205],"genre_scores_gemma":[0.9727597,0.00001641149,0.02390773,0.0001523602,0.000364148,0.0000151929,0.00007030545,0.00002550255,0.002688631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2459788,"threshold_uncertainty_score":0.4284515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01408557551642891,"score_gpt":0.256501057655725,"score_spread":0.242415482139296,"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."}}