{"id":"W2159109545","doi":"10.1109/tcbb.2006.29","title":"A Powerful Approach for Effective Finding of Significantly Differentially Expressed Genes","year":2006,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Estimator; Computer science; Set (abstract data type); Extension (predicate logic); Data mining; Expression (computer science); Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005510507,0.001463753,0.002542203,0.002855961,0.001013503,0.001689944,0.002686647,0.001871971,0.003262445],"category_scores_gemma":[0.02248757,0.001216624,0.002015615,0.002845474,0.00187835,0.002404425,0.003349715,0.003950683,0.001871754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005715826,"about_ca_system_score_gemma":0.001380961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005299505,"about_ca_topic_score_gemma":0.0005976355,"domain_scores_codex":[0.9956792,0.001398838,0.000188429,0.001158415,0.001419722,0.0001553495],"domain_scores_gemma":[0.9903764,0.006349485,0.0005184746,0.001947196,0.0006529835,0.0001553656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002613331,0.0001793957,0.002500997,0.0005063224,0.0002950864,0.000367073,0.0003089888,0.07154411,0.04578547,0.1248831,0.008411786,0.7449564],"study_design_scores_gemma":[0.0002377457,0.0003040152,0.002951195,0.00006673222,0.0001808361,0.001664538,0.00008476897,0.545113,0.03265795,0.3895145,0.02709395,0.0001306777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007479088,0.00007684738,0.9986285,0.00009658272,0.00001579306,0.00001897692,0.00003099808,0.000207149,0.0001773505],"genre_scores_gemma":[0.03057461,0.0002166676,0.9672866,0.0002403681,0.00009487547,0.0002183702,0.0002158406,0.0001449642,0.001007679],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005510507,"threshold_uncertainty_score":0.02914268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0136051692005075,"score_gpt":0.267341398799764,"score_spread":0.2537362295992565,"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."}}