{"id":"W6920922054","doi":"10.6084/m9.figshare.12082692.v1","title":"Additional file 15 of Visualizing metabolic network dynamics through time-series metabolomic data","year":2020,"lang":"en","type":"article","venue":"Figshare","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Dynamics (music); Metabolic network; Visualization; Key (lock); Artificial neural network","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001644574,0.001781104,0.001344882,0.002505612,0.0008590422,0.002391571,0.002593411,0.001384989,0.8005195],"category_scores_gemma":[0.01519077,0.0007905222,0.001206659,0.003341903,0.0003367847,0.002292287,0.001647043,0.001241994,0.1793238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001046198,"about_ca_system_score_gemma":0.001747913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007523772,"about_ca_topic_score_gemma":0.009190849,"domain_scores_codex":[0.9993809,0.00009757042,0.0000872334,0.0001595371,0.0001992341,0.00007555371],"domain_scores_gemma":[0.9905219,0.006659787,0.0005676575,0.0007024391,0.001220451,0.0003277954],"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":[0.0003997704,0.00008208073,0.001732631,0.002207727,0.00007132522,0.0001495677,0.00009757121,0.00144769,0.0005394969,0.001390386,0.9780461,0.01383557],"study_design_scores_gemma":[0.00216861,0.0001657297,0.01054564,0.001348034,0.000146006,0.0004089262,0.0002600403,0.007161188,0.004366524,0.01395413,0.9592788,0.0001964349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.0002986621,0.00003353283,0.002187212,0.0001360522,0.00005579436,0.0001067818,0.9885483,0.00672567,0.001908005],"genre_scores_gemma":[0.009689838,0.0001770817,0.01499048,0.0005134887,0.0001181175,0.001229944,0.953295,0.009367494,0.0106186],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8005195,"threshold_uncertainty_score":0.2845347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0268275706648277,"score_gpt":0.241591051030642,"score_spread":0.2147634803658143,"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."}}