{"id":"W2154437541","doi":"10.1038/ng1033","title":"From patterns to pathways: gene expression data analysis comes of age","year":2002,"lang":"en","type":"review","venue":"Nature Genetics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":581,"is_retracted":false,"has_abstract":false,"ca_institutions":"Women's Health Research Institute","funders":"","keywords":"Biology; DNA microarray; Gene expression profiling; Computational biology; Cluster analysis; Microarray analysis techniques; Profiling (computer programming); Microarray databases; Gene expression; Bioinformatics; Microarray; Gene chip analysis; Data science; Data mining; Gene; Genetics; Computer science; Machine learning","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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0001343673,0.000428594,0.001073556,0.0002745792,0.00004446575,0.00003427574,0.00161036,0.001308142,0.0001105566],"category_scores_gemma":[0.00006989002,0.0003550306,0.0004291797,0.0005686447,0.00003167493,0.000002464314,0.0008918969,0.0004016302,0.00001351321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002329624,"about_ca_system_score_gemma":0.0001013397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008967257,"about_ca_topic_score_gemma":0.0000247759,"domain_scores_codex":[0.9974201,0.0001744151,0.000630041,0.001150408,0.000380371,0.0002446888],"domain_scores_gemma":[0.9959074,0.00002432823,0.0004796089,0.003309079,0.0001080649,0.0001715215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002087673,0.0001850525,0.0003488481,0.001555759,0.001341207,0.00001019637,0.0000913055,0.00005885831,0.03327559,0.000001616695,0.04662742,0.9164833],"study_design_scores_gemma":[0.0001260058,0.00005296234,0.0002228354,0.0007169817,0.001659683,0.000001472101,0.0000203252,0.00001169086,0.01665372,0.000005527145,0.9801444,0.0003844265],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001253877,0.990408,0.003171003,0.00001269156,0.0004132988,0.0004181596,0.004210291,0.00001224052,0.0001004602],"genre_scores_gemma":[0.003366415,0.9704598,0.005502951,0.0001167066,0.0007783433,0.00004497049,0.01930461,0.00006232276,0.0003638702],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.933517,"threshold_uncertainty_score":0.9999884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0686333173855451,"score_gpt":0.348058894037556,"score_spread":0.279425576652011,"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."}}