{"id":"W1579957049","doi":"10.1002/9780471740360.ebs1323","title":"Gene Expression Profiles, Nonlinear System Identification In","year":2006,"lang":"en","type":"other","venue":"Wiley Encyclopedia of Biomedical Engineering","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Identification (biology); Computer science; Expression (computer science); Focus (optics); Class (philosophy); Data mining; Nonlinear system; Machine learning; Microarray analysis techniques; Computational biology; Artificial intelligence; Gene; Gene expression; Biology; 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":[0.0001408372,0.000233708,0.0002697016,0.0003606127,0.00001125077,0.000007309955,0.0002543677,0.0005491333,0.00002981158],"category_scores_gemma":[0.00004985015,0.0002259751,0.00007569836,0.0002321833,0.00004669727,0.000002563392,0.00007551655,0.0001420368,0.000009337757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003778797,"about_ca_system_score_gemma":0.00008789822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005637483,"about_ca_topic_score_gemma":0.000008500662,"domain_scores_codex":[0.9985406,0.00002863173,0.0004792819,0.0004385426,0.0002984082,0.0002145371],"domain_scores_gemma":[0.999188,0.000006141755,0.0002456747,0.0004386459,0.00002671372,0.00009478975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001214879,0.00009239142,0.0001297575,0.0005684167,0.00001652578,0.000004706406,0.00001041224,0.0001139468,0.7366588,0.00001174524,0.2597067,0.00267446],"study_design_scores_gemma":[0.000421596,0.00003731945,0.0003209093,0.001009047,0.00001403939,0.000004216519,0.00001799604,0.000736787,0.1019646,6.672112e-7,0.8951876,0.0002852655],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04102419,0.06567869,0.2479344,0.0003487777,0.01698041,0.006957821,0.002448361,0.001636997,0.6169904],"genre_scores_gemma":[0.2392701,0.02455326,0.07860167,0.00009015891,0.01764614,0.001942538,0.02640233,0.003352913,0.6081409],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6354809,"threshold_uncertainty_score":0.9214998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003758809165235251,"score_gpt":0.2102116598880797,"score_spread":0.2064528507228445,"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."}}