{"id":"W2738012634","doi":"10.7490/f1000research.1112918.1","title":"Survival prediction using microarray data – A topic modeling approach","year":2016,"lang":"en","type":"article","venue":"Faculty of 1000 Research Ltd","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Open peer review; Plant biology; Microarray analysis techniques; Computational biology; Computer science; Medicine; Data science; Bioinformatics; Biology; Gene expression; 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":[],"consensus_categories":[],"category_scores_codex":[0.0009511331,0.00008118716,0.00009832456,0.00007771951,0.0001013105,0.00001788557,0.0005102523,0.0001197137,0.00002681476],"category_scores_gemma":[0.0001718212,0.00005712549,0.00003663786,0.0001304553,0.0001024966,0.00001125343,0.0003348497,0.00008856465,0.000006797249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003233059,"about_ca_system_score_gemma":0.0001767166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008127166,"about_ca_topic_score_gemma":0.000008435333,"domain_scores_codex":[0.9985269,0.0001786833,0.0001866641,0.0004434197,0.0004187966,0.0002454771],"domain_scores_gemma":[0.9986904,0.00001056403,0.00004499184,0.0008074184,0.0003683308,0.00007830931],"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":[0.00005583482,0.00004836607,0.0009999202,0.00002183764,0.00001907643,1.457607e-7,0.00002844605,0.0001533955,0.9888411,0.0000293341,0.00532426,0.004478282],"study_design_scores_gemma":[0.001676197,0.0002282334,0.001938142,0.0001613469,0.00001815687,0.000009232079,0.0008208164,0.0346102,0.8046117,0.0001397569,0.1554843,0.0003019603],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8396755,0.0004069476,0.155046,0.0008637632,0.0001509366,0.0002870747,0.0006061816,0.00001698186,0.002946685],"genre_scores_gemma":[0.9929883,0.0001489052,0.00238312,0.000008740045,0.0002413146,0.00001169549,0.0006147184,0.00001388571,0.003589315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1842294,"threshold_uncertainty_score":0.232951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.178245223307122,"score_gpt":0.4009661126890185,"score_spread":0.2227208893818965,"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."}}