{"id":"W4285113924","doi":"10.1007/978-1-0716-2124-0_12","title":"Integrated Network Discovery Using Multi-Proteomic Data","year":2022,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brandon University","funders":"","keywords":"Systems biology; Proteome; Computational biology; Biological network; Proteomics; Biology; Reductionism; Computer science; Data science; Bioinformatics; Genetics; 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":[0.001760678,0.00154086,0.001501588,0.008651544,0.0006494488,0.003244467,0.001343602,0.0007230317,0.002047426],"category_scores_gemma":[0.005986325,0.0006209683,0.002044944,0.006575366,0.0003912877,0.00272586,0.002521119,0.001451792,0.0008366135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007957332,"about_ca_system_score_gemma":0.0009630697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001613935,"about_ca_topic_score_gemma":0.003763754,"domain_scores_codex":[0.9984096,0.0003694887,0.0001130643,0.0005578218,0.0004512034,0.00009883192],"domain_scores_gemma":[0.9963642,0.001934617,0.0004955833,0.0006511394,0.000350871,0.0002036645],"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":[0.002651587,0.001147839,0.07177804,0.005256706,0.00854727,0.002534398,0.0007789186,0.1464594,0.2511909,0.04263694,0.01206497,0.454953],"study_design_scores_gemma":[0.0001217016,0.0002252607,0.0280445,0.0002402974,0.001554045,0.001001087,0.0003665832,0.7332679,0.05007442,0.1629878,0.02197308,0.0001433597],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1463244,0.005291666,0.8131241,0.001104514,0.0001723073,0.0003147974,0.02457392,0.006080905,0.003013437],"genre_scores_gemma":[0.4445401,0.00350121,0.513957,0.0002712008,0.0001401384,0.0004974918,0.03524786,0.0003910966,0.001453994],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008651544,"threshold_uncertainty_score":0.009311438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0519067685455491,"score_gpt":0.3835083827526055,"score_spread":0.3316016142070564,"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."}}