{"id":"W4283020854","doi":"10.21203/rs.3.pex-1919/v1","title":"Using MetaboAnalyst 5.0 Part II: Obtaining functional insights from peak list data","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Génome Québec; Genome Canada","keywords":"Computer science; Data science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004505177,0.00486152,0.002942206,0.006352608,0.001259399,0.004817524,0.002390441,0.001482766,0.03227098],"category_scores_gemma":[0.01290075,0.002212817,0.002285927,0.005857245,0.0007436986,0.002840132,0.001822313,0.002583083,0.01777185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007577066,"about_ca_system_score_gemma":0.002912914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004210661,"about_ca_topic_score_gemma":0.003762953,"domain_scores_codex":[0.9986351,0.0001928868,0.000181389,0.0004266429,0.0004110606,0.0001528703],"domain_scores_gemma":[0.9958476,0.001953679,0.0004550593,0.0009039454,0.0006463045,0.0001934679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004613759,0.0004917392,0.01801682,0.008537538,0.002416548,0.002691724,0.002353174,0.0058235,0.3646559,0.01040161,0.3163735,0.2636242],"study_design_scores_gemma":[0.0008087344,0.0008000705,0.0448811,0.0006891276,0.001280504,0.003888163,0.0006795529,0.088371,0.4934746,0.02574041,0.3384766,0.0009101587],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.02921202,0.001359037,0.2641492,0.0007494707,0.0006152224,0.0003902081,0.1619231,0.5376693,0.003932382],"genre_scores_gemma":[0.06250662,0.001442384,0.6516857,0.0003545593,0.000214138,0.001392094,0.188729,0.08942947,0.004246037],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03227098,"threshold_uncertainty_score":0.1079571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2598034446056705,"score_gpt":0.4269036985222792,"score_spread":0.1671002539166087,"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."}}