{"id":"W2604023245","doi":"10.1111/biom.12685","title":"Estimating Time-Varying Directed Gene Regulation Networks","year":2017,"lang":"en","type":"article","venue":"Biometrics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computational biology; Gene regulatory network; Gene; Biology; Genetics; Gene expression","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003485079,0.0001631681,0.000178315,0.0002837306,0.0005167943,0.0001536506,0.0003857944,0.0002072123,0.00003065822],"category_scores_gemma":[0.0004902199,0.0001691166,0.0001244827,0.0006586969,0.00007600243,0.000007987988,0.0002389766,0.0000605992,0.00002809892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002765199,"about_ca_system_score_gemma":0.00002673323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001572767,"about_ca_topic_score_gemma":0.000002324353,"domain_scores_codex":[0.9988537,0.00004536477,0.0002303571,0.0003872978,0.0001953256,0.0002879364],"domain_scores_gemma":[0.9984745,0.00001755585,0.0003084468,0.0009497474,0.0001469856,0.0001028083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003896169,0.00006966347,0.02014733,0.00001686966,0.0002885174,0.000006662862,0.00001018305,0.05922518,0.8238914,0.00001122661,0.007070572,0.08922345],"study_design_scores_gemma":[0.0005628327,0.00009008667,0.1169766,0.0000185169,0.0001248867,0.00001482192,0.000001591278,0.8134792,0.06133847,0.000052495,0.006853015,0.0004874301],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9027989,0.002051378,0.09267752,0.00006897285,0.0005979596,0.0001816466,0.000008352618,0.00008798217,0.001527287],"genre_scores_gemma":[0.9690496,0.00005696639,0.02836427,0.00003483666,0.0009686031,0.000006727667,0.0002774518,0.0000327389,0.001208835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7625529,"threshold_uncertainty_score":0.6896377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01535468137126755,"score_gpt":0.2591898043408331,"score_spread":0.2438351229695656,"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."}}