{"id":"W2605533771","doi":"","title":"油松cDNA SRAP-PCR反应体系的建立与优化","year":2016,"lang":"zh","type":"article","venue":"分子植物育种","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Complementary DNA; Biology; Genetics; Evolutionary biology; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00304614,0.001873683,0.002098138,0.002081985,0.002007886,0.002795507,0.001674465,0.001661404,0.02240315],"category_scores_gemma":[0.003506268,0.001811739,0.002305916,0.002211348,0.001890855,0.003145919,0.001618431,0.004675361,0.01941137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00144088,"about_ca_system_score_gemma":0.003600861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001070221,"about_ca_topic_score_gemma":0.001599012,"domain_scores_codex":[0.9939764,0.001070453,0.0006738474,0.00230586,0.001449371,0.0005240767],"domain_scores_gemma":[0.9965724,0.0008748259,0.0002494796,0.0004722594,0.00159805,0.0002330116],"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":[0.0004413284,0.0003065587,0.00157149,0.001878333,0.00006975634,0.0003100662,0.0007163467,0.000391206,0.9301339,0.007353618,0.005559981,0.05126748],"study_design_scores_gemma":[0.0001321895,0.0005973384,0.003081614,0.0003379062,0.0002637588,0.0008441441,0.0004871195,0.003969502,0.8397574,0.004419512,0.1459865,0.000122944],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1076778,0.004417326,0.7902211,0.002408542,0.003124268,0.004350327,0.01554984,0.007697462,0.06455322],"genre_scores_gemma":[0.1014372,0.003624327,0.7846203,0.002312929,0.0005749701,0.006647215,0.02409798,0.002757025,0.07392796],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02240315,"threshold_uncertainty_score":0.07494599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01292312524122975,"score_gpt":0.2197227803161476,"score_spread":0.2067996550749179,"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."}}