{"id":"W4283075502","doi":"10.21203/rs.3.pex-1921/v1","title":"Using MetaboAnalyst 5.0 Part IV: Analyzing metabolomics data with complex metadata","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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":"Metadata; Computer science; Exploratory analysis; Data science; World Wide Web","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":[0.006669547,0.004245113,0.002457848,0.006424476,0.001094581,0.006360219,0.002511425,0.001460685,0.03048824],"category_scores_gemma":[0.02176378,0.002409723,0.002699191,0.006042537,0.0008619554,0.003936555,0.003279572,0.002851931,0.01740249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009604311,"about_ca_system_score_gemma":0.004132716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004664107,"about_ca_topic_score_gemma":0.004321936,"domain_scores_codex":[0.9975682,0.0003967414,0.0004107705,0.0005727117,0.0008682934,0.0001832236],"domain_scores_gemma":[0.9925253,0.003058049,0.000691266,0.002490309,0.0009585702,0.0002764536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002972555,0.0004305044,0.01947669,0.00784178,0.003394184,0.002705105,0.00169907,0.01328715,0.09022846,0.02505508,0.5677283,0.2651811],"study_design_scores_gemma":[0.000912212,0.0004148491,0.01942269,0.00114561,0.00110597,0.002348481,0.0005753976,0.09159455,0.1957376,0.06660032,0.619373,0.0007693825],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.00619821,0.0007013736,0.2307987,0.0005824754,0.0004830378,0.0003334727,0.08795623,0.6703699,0.00257665],"genre_scores_gemma":[0.0488222,0.001422245,0.5970866,0.0005550879,0.0003508086,0.001399089,0.2097547,0.1349486,0.005660668],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.03048824,"threshold_uncertainty_score":0.1019934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2480556912672757,"score_gpt":0.4403995015940147,"score_spread":0.192343810326739,"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."}}