{"id":"W2369326609","doi":"","title":"Reconstruction of genetic regulatory network from omics data","year":2010,"lang":"en","type":"article","venue":"China Journal of Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Gene regulatory network; Bayesian network; Computational biology; Computer science; Biomedicine; Biological network; Artificial life; Systems biology; Biology; Gene; Theoretical computer science; Artificial intelligence; Data science; Genetics","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":[0.0005194766,0.0001465401,0.0003048342,0.00007466842,0.00005734191,0.00002264993,0.0006862838,0.0001989828,0.00003266559],"category_scores_gemma":[0.0001020242,0.0001288954,0.0001571723,0.0001376134,0.0001473921,0.00002560176,0.0002150956,0.00024574,0.000002722087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008850794,"about_ca_system_score_gemma":0.0001770302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004598709,"about_ca_topic_score_gemma":0.0000226199,"domain_scores_codex":[0.9985074,0.00003512451,0.0009363574,0.0001167653,0.0002256697,0.0001786931],"domain_scores_gemma":[0.9975283,0.00001590174,0.001168994,0.0009909881,0.0001791838,0.0001166649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000417605,0.0001998544,0.1552691,0.0001781339,0.002293116,0.00001072895,0.0005433617,0.03837418,0.3759188,0.0001235412,0.03272365,0.3939479],"study_design_scores_gemma":[0.005109032,0.001396029,0.4994852,0.0004096891,0.002230246,0.002716418,0.0008889427,0.2139202,0.2002436,0.005513108,0.06623985,0.001847686],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879147,0.0009963589,0.009903813,0.00003087053,0.0008664381,0.0000556866,0.00003952797,0.000003161279,0.0001894274],"genre_scores_gemma":[0.8498212,0.0005206466,0.1482307,0.00003836605,0.001232835,2.732135e-7,0.000116264,0.00001719547,0.0000225335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3921002,"threshold_uncertainty_score":0.5256202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007905341687873928,"score_gpt":0.217805065736015,"score_spread":0.2098997240481411,"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."}}