{"id":"W2062364627","doi":"10.1039/c4mb00700j","title":"An integrated metabolomics approach for the research of new cerebrospinal fluid biomarkers of multiple sclerosis","year":2015,"lang":"en","type":"article","venue":"Molecular BioSystems","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Excellence in Mining Innovation","funders":"Ministero della Salute; Fondazione Italiana Sclerosi Multipla","keywords":"Multiple sclerosis; Metabolomics; Lipidomics; Cerebrospinal fluid; Disease; Biomarker discovery; Myelin; Medicine; Bioinformatics; Computational biology; Chemistry; Proteomics; Biology; Internal medicine; Immunology; Biochemistry; Central nervous system","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":[0.001012829,0.001040756,0.001105999,0.002860674,0.0002747418,0.001184345,0.0005317022,0.0005769856,0.001441103],"category_scores_gemma":[0.0008739254,0.0003406236,0.001105056,0.002191665,0.0002446416,0.0007709056,0.0009032544,0.0006358196,0.0003986046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004237632,"about_ca_system_score_gemma":0.0007987726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001763501,"about_ca_topic_score_gemma":0.002545937,"domain_scores_codex":[0.999689,0.00008955395,0.0000213208,0.00009817321,0.0000703652,0.00003169899],"domain_scores_gemma":[0.9997924,0.00006457945,0.00003660659,0.00001977027,0.00006192111,0.00002470834],"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":[0.001627003,0.0007611117,0.02157662,0.001065348,0.002038226,0.0005307319,0.0002357747,0.02464671,0.6319411,0.003629098,0.001006261,0.3109421],"study_design_scores_gemma":[0.0001974065,0.003041412,0.1255076,0.0001813462,0.002234145,0.001520419,0.0006507711,0.6853475,0.1421244,0.02508079,0.01377916,0.0003351122],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1959774,0.006685859,0.7902609,0.0004840237,0.00009241101,0.0004609284,0.002270525,0.001722328,0.002045607],"genre_scores_gemma":[0.411672,0.003522513,0.5807028,0.0002779998,0.00009343273,0.0004822105,0.001831199,0.0001514298,0.001266455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002860674,"threshold_uncertainty_score":0.005356431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.242831453175347,"score_gpt":0.3798221349857693,"score_spread":0.1369906818104223,"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."}}