{"id":"W4387915637","doi":"10.1007/978-3-031-39094-4_2","title":"Network Development and Comparison in Lipidomics and Metabolomics","year":2023,"lang":"en","type":"book-chapter","venue":"Metabolomics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; University of Ottawa","funders":"","keywords":"Metabolomics; Lipidomics; Biological network; Computer science; Computational biology; Systems biology; Data science; Network analysis; Process (computing); Biological data; Data mining; Bioinformatics; Biology; Engineering","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"],"consensus_categories":[],"category_scores_codex":[0.0005936721,0.0004823257,0.0007767757,0.0001084832,0.0001045552,0.00006924181,0.0002069462,0.0008005464,0.00000683504],"category_scores_gemma":[0.00002137121,0.0004980274,0.00007826522,0.00003954813,0.0001561324,0.000004827175,0.0005439808,0.0004518255,0.00003255988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002299091,"about_ca_system_score_gemma":0.0001269567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000397193,"about_ca_topic_score_gemma":0.000165533,"domain_scores_codex":[0.9981093,0.00002158754,0.0007753439,0.0005298176,0.0001270776,0.000436835],"domain_scores_gemma":[0.9990845,0.00003700798,0.0003181485,0.0003768921,0.00004470721,0.0001386858],"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":[0.001459456,0.0001721165,0.00714904,0.000952029,0.003142959,0.0000623787,0.002160782,0.008990755,0.00223421,0.3785608,0.09739108,0.4977244],"study_design_scores_gemma":[0.0009904994,0.00006760768,0.0005789017,0.00007111872,0.0001363533,0.00001839549,0.00005267031,0.001642145,0.0002242178,0.007989821,0.9873687,0.0008595721],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.4751965,0.2509298,0.01138679,0.0009710893,0.009187635,0.006096694,0.001081025,0.0003767231,0.2447737],"genre_scores_gemma":[0.06898247,0.1631815,0.142787,0.006087491,0.007729146,0.0002566157,0.008867169,0.001313497,0.6007951],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8899776,"threshold_uncertainty_score":0.9997472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02078356678244498,"score_gpt":0.2313535721298068,"score_spread":0.2105700053473619,"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."}}