{"id":"W4318472573","doi":"10.37867/te1401141","title":"GENOME-WIDE IDENTIFICATION OF NICOTIANA TABACUM MIRNAS AND THEIR ROLE IN HUMAN HEALTH – A COMPUTATIONAL GENOMICS ASSESSMENT","year":2022,"lang":"en","type":"article","venue":"Towards Excellence","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Nicotiana tabacum; Genome; Biology; microRNA; Identification (biology); Genomics; Computational biology; Biotechnology; Genetics; Botany; Gene","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":[0.0003008682,0.00008119189,0.0001107925,0.00005141087,0.00008533269,0.000008175555,0.0001275064,0.00001847912,0.00001365794],"category_scores_gemma":[0.000005980988,0.00009066903,0.00002907968,0.00006666907,0.00003144455,0.000001970075,0.0001533065,0.0000754865,2.125508e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004775178,"about_ca_system_score_gemma":0.0001153411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008915877,"about_ca_topic_score_gemma":0.00002561254,"domain_scores_codex":[0.9992708,0.00004505368,0.0002499324,0.0002127349,0.00009394232,0.0001275113],"domain_scores_gemma":[0.9996912,0.000007555976,0.00008953649,0.0001511192,0.00002182556,0.00003875157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000009351242,0.00007953597,0.003972358,0.00004623522,0.00001661234,6.539129e-7,0.0008727349,0.06607763,0.9262707,0.00005962779,0.00004392154,0.002550705],"study_design_scores_gemma":[0.001197113,0.0006939474,0.7820203,0.00001996804,0.0000108883,0.00003578839,0.004955002,0.02573717,0.1755332,0.001381197,0.007911336,0.0005041101],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774207,0.001990748,0.02001877,0.0001813753,0.00004248955,0.0001550227,0.00005489132,0.000004732339,0.0001313146],"genre_scores_gemma":[0.9987403,0.0001849528,0.0007541067,0.00005503437,0.00002011333,0.00002398316,0.0001221048,0.00001027695,0.00008917282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7780479,"threshold_uncertainty_score":0.3697376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008579901545675967,"score_gpt":0.2967978915193404,"score_spread":0.2882179899736645,"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."}}