{"id":"W177627685","doi":"10.4137/gegg.s0","title":"Introductory Editorial (Gene Expression to Genetical Genomics)","year":2008,"lang":"en","type":"article","venue":"Gene Expression to Genetical Genomics","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genomics; Genetics; Biology; Gene; Computational biology; Functional genomics; Expression (computer science); Genome; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007951531,0.0007995664,0.0007236503,0.0003382515,0.0005705024,0.0001318896,0.001652643,0.001032756,0.0002430021],"category_scores_gemma":[0.0009994595,0.0007398119,0.0003551608,0.0003663905,0.0005176381,0.00001452843,0.002477698,0.0005779566,0.001066942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002134436,"about_ca_system_score_gemma":0.0008151986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001385759,"about_ca_topic_score_gemma":0.000007316461,"domain_scores_codex":[0.9933766,0.000268255,0.001325298,0.001744598,0.001509002,0.001776297],"domain_scores_gemma":[0.9945757,0.00008234559,0.0001762402,0.001965557,0.0005626876,0.002637506],"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":[0.0006974426,0.0002147569,0.0002134266,0.00002652895,0.00003796219,0.00001464116,0.0003621459,0.0008654993,0.8092867,0.000004793856,0.1853347,0.002941358],"study_design_scores_gemma":[0.0008569248,0.0008919442,0.0007162438,0.00001947388,0.00001795349,0.00004310703,0.00006917693,0.00008135517,0.6511015,0.00005325315,0.3454935,0.0006556219],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9401608,0.0009135909,0.04400035,0.000849833,0.01167661,0.001496808,0.0002367996,0.00007813188,0.0005870748],"genre_scores_gemma":[0.5654228,0.003784101,0.3227482,0.003873942,0.09910788,0.0004143513,0.0009143913,0.0003931613,0.003341165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.374738,"threshold_uncertainty_score":0.9997109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01422179583285843,"score_gpt":0.2654452539109053,"score_spread":0.2512234580780469,"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."}}