{"id":"W4232789909","doi":"10.5376/mpb.cn.2011.09.0056","title":"洋葱种质资源遗传多样性的SSR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":"Environmental 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":[0.001091624,0.0003036362,0.0002614998,0.0009660669,0.001420898,0.004398542,0.0005236971,0.0009951798,0.02475686],"category_scores_gemma":[0.002701147,0.0001859921,0.0002605424,0.0008744477,0.00323503,0.003215113,0.0008019563,0.001038146,0.004512525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002607236,"about_ca_system_score_gemma":0.002262878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004758261,"about_ca_topic_score_gemma":0.002988058,"domain_scores_codex":[0.9993117,0.00016252,0.00003580493,0.000153824,0.0002549107,0.00008120023],"domain_scores_gemma":[0.99909,0.0002751796,0.0001161899,0.00009172029,0.0003595219,0.00006737948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001448389,0.00001873359,0.0008754487,0.0000494409,0.00001465586,0.00004947721,0.0008199387,0.0008261955,0.0004622975,0.9667504,0.003242358,0.02687656],"study_design_scores_gemma":[0.00001636148,0.00006254912,0.004822473,0.00006871662,0.00003666641,0.0001929384,0.002932207,0.002412302,0.00192048,0.8620238,0.1254802,0.00003115773],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05509447,0.001843742,0.0335326,0.00940543,0.0003927175,0.00006341458,0.0002730916,0.0001262379,0.8992683],"genre_scores_gemma":[0.8128097,0.001445088,0.009670421,0.001023651,0.0002679468,0.00006579194,0.0001357697,0.00004816449,0.1745335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02475686,"threshold_uncertainty_score":0.08281994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221342238577638,"score_gpt":0.1929140313539946,"score_spread":0.1707006089682182,"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."}}