{"id":"W2935257869","doi":"10.1093/bioinformatics/btz229","title":"<i>RTNsurvival</i>: an R/Bioconductor package for regulatory network survival analysis","year":2019,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; BC Cancer Agency","funders":"National Cancer Institute; Cancer Research UK; National Institutes of Health; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Breast Cancer Research Foundation","keywords":"Bioconductor; R package; Computer science; Survival analysis; Network analysis; Computational biology; Biology; Statistics; Mathematics; Genetics; Programming language; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007877322,0.0003104689,0.0004396918,0.00009744868,0.0001436582,0.0001075494,0.0004619184,0.0003318443,0.00007198536],"category_scores_gemma":[0.00002656803,0.0002862829,0.0003756178,0.0003442867,0.00007068061,0.00003313593,0.0001547194,0.0001194931,0.0000850189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002217133,"about_ca_system_score_gemma":0.0001043304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005241392,"about_ca_topic_score_gemma":0.00004546066,"domain_scores_codex":[0.9981572,0.00004032997,0.0006866809,0.0002847464,0.0002329688,0.0005980518],"domain_scores_gemma":[0.9981154,0.00003465235,0.0003285821,0.00115006,0.0001559522,0.0002153761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003834726,0.001643046,0.1958332,0.00412288,0.0256569,0.000007728636,0.005817343,0.1241194,0.1699223,0.1010711,0.2613525,0.106619],"study_design_scores_gemma":[0.007153334,0.003251616,0.03025928,0.00008199091,0.002044666,0.00002580948,0.002529458,0.2823303,0.01308419,0.002471582,0.652553,0.004214862],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8714567,0.000380464,0.1152319,0.00006696691,0.001857583,0.001469824,0.0003330839,0.00008867698,0.009114795],"genre_scores_gemma":[0.951591,0.00008564811,0.04060409,0.001031338,0.001126922,0.00005250493,0.003151846,0.00007016352,0.002286557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3912004,"threshold_uncertainty_score":0.9999589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01304330957016848,"score_gpt":0.2410637046180571,"score_spread":0.2280203950478886,"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."}}