{"id":"W2345627546","doi":"10.1101/051508","title":"System-wide quantitative proteomics of the metabolic syndrome in mice: genotypic and dietary effects","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"European Commission","keywords":"Compendium; Proteomics; Proteome; Systems biology; Metabolomics; Biology; Computational biology; Mass spectrometry; Bioinformatics; Biochemistry; Chemistry; Gene; Chromatography","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":[0.001947105,0.0006305691,0.0006869498,0.001024831,0.0003513183,0.0008992039,0.0004279203,0.0004014778,0.0007250624],"category_scores_gemma":[0.000734166,0.0003613342,0.0007331186,0.0009543748,0.0005379649,0.0004020912,0.0007778636,0.0009158851,0.0002051661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004662423,"about_ca_system_score_gemma":0.0004880804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000847687,"about_ca_topic_score_gemma":0.001421141,"domain_scores_codex":[0.9990684,0.0001800564,0.00008790316,0.000228346,0.000370711,0.00006454254],"domain_scores_gemma":[0.9990408,0.0002163409,0.0002692727,0.0002176681,0.0001755651,0.00008039314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003334873,0.00003328289,0.00423602,0.0001089478,0.0001468008,0.00003038545,0.00002219105,0.000875247,0.9899579,0.0002336933,0.0002755632,0.003746426],"study_design_scores_gemma":[0.00005864384,0.0004121152,0.09602864,0.00002747829,0.0003064117,0.0003561187,0.00005985783,0.009283854,0.8872709,0.001197917,0.004921783,0.00007631046],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9187412,0.001434626,0.06441096,0.0005002042,0.00006889064,0.0001048359,0.01301675,0.0009357334,0.0007868236],"genre_scores_gemma":[0.8681551,0.001879627,0.1076277,0.0006144128,0.00005269534,0.0005434378,0.01871652,0.0006829133,0.001727576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001947105,"threshold_uncertainty_score":0.01029742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01014742138708375,"score_gpt":0.2323210927692527,"score_spread":0.2221736713821689,"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."}}