{"id":"W4235734085","doi":"10.5376/mpb.cn.2011.09.0041","title":"农家遗存稻谷古DNA提取及PCR分析","year":2011,"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":false,"ca_institutions":"","funders":"","keywords":"Computational biology; Computer science; Biology; Molecular biology","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":[0.002111143,0.001167843,0.001318866,0.001716693,0.001684855,0.002479709,0.001115407,0.0014319,0.01064994],"category_scores_gemma":[0.0037458,0.001506461,0.001382225,0.001020864,0.00273071,0.001725091,0.001016944,0.002486874,0.01096898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001283124,"about_ca_system_score_gemma":0.002233876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002004241,"about_ca_topic_score_gemma":0.002976602,"domain_scores_codex":[0.9967735,0.000704908,0.0002132481,0.001162727,0.0008422689,0.0003032454],"domain_scores_gemma":[0.9977146,0.0008315179,0.0001759995,0.0003623837,0.0007854535,0.0001300017],"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":[0.0003816013,0.0002826279,0.005747715,0.001180394,0.0001368691,0.0004293058,0.001842656,0.001094114,0.8470207,0.0336636,0.004348756,0.1038717],"study_design_scores_gemma":[0.00004031288,0.000339666,0.003384845,0.0001721116,0.000281219,0.000521533,0.0005371069,0.002301555,0.8911061,0.008103956,0.09313001,0.00008176998],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1413147,0.003276839,0.7622299,0.002326021,0.00200865,0.001540571,0.003267812,0.002794948,0.08124053],"genre_scores_gemma":[0.2629124,0.002678865,0.6260816,0.002754542,0.0003123723,0.001969685,0.004671548,0.0009312556,0.09768774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01064994,"threshold_uncertainty_score":0.0356276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02353476717898089,"score_gpt":0.1932566901749494,"score_spread":0.1697219229959685,"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."}}