{"id":"W7143690763","doi":"10.15083/0002004769","title":"イネの葉の形態形成に関する分子遺伝学的研究","year":2020,"lang":"en","type":"dissertation","venue":"Institutional Repositories DataBase (IRDB)","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Agriculture and Food Research Organization; Institute of Genetics; University of Tokyo","keywords":"Process (computing); Work (physics); Product (mathematics); Set (abstract data type); Information system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001578711,0.0003102157,0.0002980778,0.001798154,0.002218159,0.005232501,0.0003053687,0.0006421473,0.09107087],"category_scores_gemma":[0.002607587,0.0002486496,0.0002025784,0.002851346,0.001466963,0.002950159,0.001295037,0.001142592,0.0281654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002536075,"about_ca_system_score_gemma":0.005975981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005768489,"about_ca_topic_score_gemma":0.01407181,"domain_scores_codex":[0.9991471,0.0001074527,0.00006489072,0.0001453169,0.0004323132,0.0001029371],"domain_scores_gemma":[0.9980664,0.000221635,0.000152023,0.0001374421,0.0009544049,0.0004680133],"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":[0.0002462608,0.0002007377,0.01265425,0.0008704925,0.00002264936,0.0003097482,0.01375986,0.000428114,0.006595024,0.1203979,0.329371,0.515144],"study_design_scores_gemma":[0.00001973464,0.00004850308,0.01999569,0.0002993815,0.00001916214,0.0001731305,0.005375763,0.0001839626,0.002775895,0.008864563,0.9622223,0.00002192375],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02913202,0.006386848,0.004509754,0.01008079,0.001120362,0.0002007713,0.002810827,0.0003241154,0.9454345],"genre_scores_gemma":[0.1879466,0.01242009,0.01157601,0.001202097,0.000804095,0.0003027672,0.003368958,0.0003511496,0.7820282],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09107087,"threshold_uncertainty_score":0.3046624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01043300440381056,"score_gpt":0.2276569481113109,"score_spread":0.2172239437075003,"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."}}