{"id":"W2097185378","doi":"10.1093/bioinformatics/btr392","title":"MetATT: a web-based metabolomics tool for analyzing time-series and two-factor datasets","year":2011,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"Genome Alberta; Alberta Innovates","keywords":"Principal component analysis; Computer science; Metabolomics; Visualization; Data mining; Multivariate statistics; Time series; Session (web analytics); Identification (biology); Series (stratigraphy); Bioinformatics; Machine learning; Artificial intelligence; Biology","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":[0.003421677,0.002679613,0.001730529,0.005722628,0.0007533765,0.002476513,0.002603394,0.001430883,0.04925218],"category_scores_gemma":[0.009573015,0.00135963,0.002564224,0.005301173,0.0003330173,0.002736315,0.002860006,0.002067649,0.01461794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005421304,"about_ca_system_score_gemma":0.001417107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002027324,"about_ca_topic_score_gemma":0.003331929,"domain_scores_codex":[0.999088,0.0001921972,0.0001468039,0.0002061617,0.000306916,0.00005981652],"domain_scores_gemma":[0.9949806,0.003177405,0.0004496979,0.0006695676,0.0004711073,0.0002515718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003104208,0.0005696167,0.01559679,0.005965344,0.002064705,0.002178061,0.0008945601,0.01523479,0.05183085,0.01087761,0.5125134,0.3791701],"study_design_scores_gemma":[0.001504253,0.0005636897,0.03399503,0.0008925262,0.0008604945,0.002660762,0.0004548668,0.2617574,0.07123938,0.08455405,0.5406123,0.0009052933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.005372092,0.0004616311,0.4469121,0.0004049367,0.0002065385,0.0003846214,0.1252613,0.4187241,0.002272729],"genre_scores_gemma":[0.04913583,0.0007966605,0.6996011,0.0005780659,0.0002380532,0.003574988,0.2022292,0.03876116,0.005084953],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04925218,"threshold_uncertainty_score":0.1647649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01831110162887262,"score_gpt":0.2474766800421787,"score_spread":0.229165578413306,"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."}}