{"id":"W104697757","doi":"","title":"葉緑体のRNAエディティング部位の網羅的同定と新しいin vitro RNAエディティング系を用いたシス配列の解析(平成16年度博士論文)","year":2005,"lang":"ja","type":"article","venue":"Canadian parliamentary review","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"RNA; In vitro; Chemistry; Molecular biology; Cell biology; Biology; Biochemistry; 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":[0.00695308,0.0005168252,0.0006823055,0.002818428,0.001755219,0.002163856,0.001156634,0.001899111,0.007704679],"category_scores_gemma":[0.005496873,0.0003731512,0.0005554622,0.002405687,0.001697535,0.0009982336,0.000538395,0.00146109,0.002206081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01184464,"about_ca_system_score_gemma":0.03344707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3160026,"about_ca_topic_score_gemma":0.5236448,"domain_scores_codex":[0.9962887,0.0005572766,0.0002860454,0.000188027,0.002289862,0.0003902121],"domain_scores_gemma":[0.9950806,0.001358367,0.0003647905,0.0001525881,0.002904792,0.0001387958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003257991,0.0001174388,0.001096341,0.01817987,0.0001466886,0.0004940734,0.0009371888,0.0005847294,0.02026812,0.05001349,0.4093527,0.4984836],"study_design_scores_gemma":[0.00001619595,0.00004351093,0.0009267916,0.001191383,0.00006665439,0.00008777931,0.00017216,0.00001643501,0.0040781,0.0006233066,0.9927661,0.00001143961],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.004127857,0.8574097,0.001206563,0.0249491,0.004922102,0.0002152963,0.0006816514,0.00003541901,0.1064523],"genre_scores_gemma":[0.04781696,0.8581269,0.003698694,0.01230644,0.0009414725,0.0002238189,0.0005873478,0.00003408513,0.07626416],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3160026,"threshold_uncertainty_score":0.6283265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01395785219998137,"score_gpt":0.2256788836862402,"score_spread":0.2117210314862588,"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."}}