{"id":"W4390457201","doi":"10.1101/2023.12.30.573613","title":"Integrating multiple omics levels using the human protein complexome as a framework, a multi-omics study of inborn errors of metabolism","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Metabolism and Genetic Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"IONICS Mass Spectrometry (Canada)","funders":"Vlaamse regering; KU Leuven; Fonds Wetenschappelijk Onderzoek","keywords":"Proteomics; Computational biology; Metabolomics; Biology; Omics; Proteome; Systems biology; Histone; Epigenetics; Bioinformatics; Biochemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001464652,0.0009761461,0.001133744,0.003993822,0.0004773647,0.002765766,0.0004777971,0.0006215847,0.001188339],"category_scores_gemma":[0.001744689,0.0003144005,0.001392519,0.003449943,0.0003754368,0.001144223,0.002050268,0.0008960092,0.000345622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008015815,"about_ca_system_score_gemma":0.000968386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002051238,"about_ca_topic_score_gemma":0.003112328,"domain_scores_codex":[0.9990129,0.0003315627,0.00009299558,0.0003088012,0.0001999708,0.00005366498],"domain_scores_gemma":[0.9991282,0.0002956791,0.0001404747,0.0002239035,0.0001402878,0.00007157504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0009359026,0.0003027403,0.08874329,0.00360595,0.003305972,0.001525623,0.0005656468,0.03785148,0.6992912,0.01474249,0.005443151,0.1436865],"study_design_scores_gemma":[0.00009083562,0.0006496978,0.3389868,0.001016156,0.002158585,0.002257091,0.001624286,0.3111092,0.1667694,0.1000961,0.07492131,0.0003205222],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4402162,0.02127883,0.4776632,0.003399397,0.0002970794,0.0003890964,0.04914021,0.002494756,0.005121186],"genre_scores_gemma":[0.6952829,0.007396145,0.2746058,0.0007596727,0.0002003487,0.000316554,0.02005933,0.0002266099,0.001152698],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003993822,"threshold_uncertainty_score":0.007745922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05573899953437254,"score_gpt":0.296242023248004,"score_spread":0.2405030237136314,"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."}}