{"id":"W2391023158","doi":"","title":"Application of in silico cloning technique in plant gene engineering","year":2006,"lang":"en","type":"article","venue":"Dongbei Nongye Daxue xuebao","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"In silico; Cloning (programming); Computational biology; Gene; Molecular cloning; Biology; Genome engineering; Genome; Genetics; Computer science; Bioinformatics; Genome editing; Gene expression; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004408994,0.0001379503,0.0001847034,0.000215845,0.00001766069,0.00001408161,0.0002449555,0.0002250295,0.000003852614],"category_scores_gemma":[0.00009267644,0.0001365896,0.00005057208,0.0002592006,0.00006737193,0.000005658228,0.0001161684,0.0001602944,0.000005375673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003420701,"about_ca_system_score_gemma":0.00006121882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005784389,"about_ca_topic_score_gemma":0.0004861342,"domain_scores_codex":[0.9987439,0.00002419474,0.0004523063,0.0002347738,0.000208907,0.0003359289],"domain_scores_gemma":[0.9994933,0.00002188279,0.00007769495,0.0002989866,0.0000479611,0.00006019301],"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":[0.0000376196,0.0001060135,0.0223867,0.00009713059,0.000006348702,0.000005862896,0.00003959299,0.001096932,0.9740313,0.0001068798,0.000138077,0.001947565],"study_design_scores_gemma":[0.0006167461,0.0001319291,0.03751197,0.00005045202,0.00000351466,0.00001180109,0.00002913685,0.008187435,0.9415763,0.00008399793,0.01157887,0.0002178526],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980438,0.0003104683,0.01774885,0.00006125711,0.00005269724,0.0004743668,0.00005286912,0.00001279767,0.0008487231],"genre_scores_gemma":[0.9949487,0.0001079322,0.004164947,0.00002497156,0.0001152315,0.00009799701,0.0004478928,0.00001591196,0.00007639571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03245498,"threshold_uncertainty_score":0.5569962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005478006558417762,"score_gpt":0.2361390352961096,"score_spread":0.2306610287376918,"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."}}