{"id":"W4360779909","doi":"10.1007/978-1-0716-3048-8","title":"Peroxisomes","year":2023,"lang":"en","type":"book","venue":"Methods in molecular biology","topic":"Peroxisome Proliferator-Activated Receptors","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Faculty of Medicine and Dentistry, University of Alberta; Indian Institute of Technology Indore; Universidade do Porto; KU Leuven; Universiteit van Amsterdam; Universität Wien; University of Exeter; Rijksuniversiteit Groningen; Amsterdam University Medical Centers; International Business Machines Corporation; Deutsches Zentrum für Herz-Kreislaufforschung; Kalinga Institute of Industrial Technology; Universidade de Aveiro; Universität Bielefeld; Medizinische Universität Wien; University of Alberta","keywords":"Peroxisome; Chemistry; Computational biology; Biology; Biochemistry; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003270897,0.002066597,0.001212187,0.002962508,0.001036343,0.003212887,0.001376719,0.001375929,0.1447029],"category_scores_gemma":[0.0002825287,0.0008087661,0.0008658849,0.001981132,0.0006200496,0.002290484,0.001663309,0.002791909,0.3374483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007411276,"about_ca_system_score_gemma":0.0007026059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008048379,"about_ca_topic_score_gemma":0.001810469,"domain_scores_codex":[0.9996699,0.00001825858,0.00001302996,0.00009810834,0.0001662508,0.00003444643],"domain_scores_gemma":[0.9998633,0.0000142353,0.00001219829,0.00003890885,0.00004004996,0.0000313789],"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":[0.0002385846,0.00007757855,0.0001502797,0.001281223,0.00004429678,0.0004169741,0.0001440564,0.0002579019,0.09655809,0.05867464,0.3873047,0.4548517],"study_design_scores_gemma":[0.000006083303,0.00001344981,0.0001162742,0.00005060013,0.000006351979,0.0003530995,0.00001134527,0.00004638504,0.00577209,0.002752063,0.990867,0.000005273197],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.00218543,0.07374923,0.04276448,0.002744276,0.004231038,0.0003057826,0.01252893,0.007284848,0.854206],"genre_scores_gemma":[0.003510659,0.01623137,0.007245204,0.0006286658,0.000261975,0.0001185245,0.007970775,0.0004000064,0.9636328],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1447029,"threshold_uncertainty_score":0.4840795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0218230490521767,"score_gpt":0.3774868310429829,"score_spread":0.3556637819908062,"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."}}