{"id":"W4394319980","doi":"10.6084/m9.figshare.22603481","title":"Additional file 2 of A functional gene module identification algorithm in gene expression data based on genetic algorithm and gene ontology","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Gene; Identification (biology); Algorithm; Computer science; Gene expression; Gene ontology; Computational biology; Genetics; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001350808,0.001822087,0.001432101,0.002631852,0.0007796841,0.001843503,0.00217661,0.001614056,0.4647914],"category_scores_gemma":[0.008332602,0.0007890452,0.001330805,0.003910882,0.0003956087,0.00146922,0.001324332,0.001564129,0.1257463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001459652,"about_ca_system_score_gemma":0.001945467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007003278,"about_ca_topic_score_gemma":0.01391955,"domain_scores_codex":[0.9992977,0.00008945591,0.00009772292,0.0002506031,0.000151583,0.000112951],"domain_scores_gemma":[0.9951793,0.002993004,0.0003059328,0.000567205,0.000698973,0.0002556079],"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":[0.0002249448,0.00009400589,0.002785475,0.001811627,0.00006990137,0.00006615245,0.00003501061,0.0006726235,0.0004051749,0.0007044396,0.9881026,0.005028027],"study_design_scores_gemma":[0.002504183,0.0001542986,0.01927932,0.000906601,0.0001785984,0.0004059416,0.0001494394,0.002261601,0.00209496,0.007227185,0.9647323,0.0001055261],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009001155,0.00001249606,0.0001246321,0.00002350368,0.000007076454,0.00001601762,0.9992396,0.000277719,0.0002090043],"genre_scores_gemma":[0.001064553,0.0000280699,0.0009192625,0.00008251375,0.00000924405,0.000226349,0.9967166,0.0002026,0.0007507519],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4647914,"threshold_uncertainty_score":0.76341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03904930769506572,"score_gpt":0.2700354592441532,"score_spread":0.2309861515490875,"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."}}