{"id":"W4389033069","doi":"10.5376/rgg.2023.14.0003","title":"Molecular Mechanism Analysis of Improving the Development of Rice Growth Organs Using Gene Editing Technology","year":2023,"lang":"en","type":"article","venue":"Rice Genomics and Genetics","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"CRISPR; Biotechnology; Biology; Genome editing; Food security; Panicle; Agriculture; Gene; Agronomy; Ecology; Genetics","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":[0.0002969415,0.0005441253,0.0002440745,0.0002389437,0.0002466659,0.0003611784,0.000465006,0.0005076324,0.001385522],"category_scores_gemma":[0.0001764402,0.0001783794,0.0006457868,0.0001089607,0.0003771998,0.0004184784,0.0002886287,0.0007245467,0.0003385404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004002645,"about_ca_system_score_gemma":0.0004089661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007612692,"about_ca_topic_score_gemma":0.0004805462,"domain_scores_codex":[0.9998448,0.00001665708,0.00001273815,0.00004776736,0.00004209509,0.00003595632],"domain_scores_gemma":[0.9999298,0.00001264106,0.00002198343,0.00000948382,0.00001388526,0.00001227883],"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":[0.00004926637,0.00002070203,0.0002703059,0.0002354677,0.0000148104,0.0002097841,0.00002708068,0.0004408739,0.9915211,0.002750799,0.000198531,0.004261194],"study_design_scores_gemma":[0.00004405847,0.0003179334,0.002959031,0.00002884613,0.00008183274,0.0007249298,0.0000488117,0.006516807,0.9720995,0.001213395,0.01593219,0.00003265083],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6887319,0.0329884,0.2346189,0.002657481,0.00095128,0.000525849,0.001198853,0.0019274,0.03640002],"genre_scores_gemma":[0.9550374,0.008732837,0.02830371,0.0003789885,0.00003365463,0.0001405755,0.0004203316,0.00006521252,0.006887185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001385522,"threshold_uncertainty_score":0.004634976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007635061575950787,"score_gpt":0.2475618566027648,"score_spread":0.239926795026814,"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."}}