{"id":"W4415548186","doi":"10.1021/acs.analchem.5c04612","title":"High-Frequency Microfluidic Fractionation for Compound-Resolved Bioactivity-Based Metabolomics","year":2025,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"thermodynamics and calorimetric analyses","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"National Institute of General Medical Sciences; Office of Science; Joint Genome Institute; Simons Foundation; Deutsche Forschungsgemeinschaft; Science Foundation Ireland; National Institute of Diabetes and Digestive and Kidney Diseases; U.S. Department of Energy","keywords":"Metabolomics; Metabolome; Microfluidics; Fractionation; Metabolite; Bioanalysis; Mass spectrometry; Bioreporter","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":[0.0005585667,0.0007331808,0.0004763129,0.000554745,0.0002390841,0.00061819,0.0005578046,0.0005024928,0.001169545],"category_scores_gemma":[0.0005532146,0.0002622891,0.000387182,0.000309827,0.0003077234,0.0004526747,0.0005032833,0.0006955264,0.0007538591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005430388,"about_ca_system_score_gemma":0.0004408674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004463881,"about_ca_topic_score_gemma":0.0008594417,"domain_scores_codex":[0.9995859,0.00004332433,0.00004779664,0.0001322696,0.0001354943,0.00005523165],"domain_scores_gemma":[0.9997078,0.0001234739,0.0000508354,0.00003748692,0.00005352121,0.00002685588],"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":[0.00002109165,0.00002200713,0.0001365834,0.0000491773,0.000004531905,0.00001756043,0.000009251198,0.0001547882,0.9953207,0.0001107494,0.0001099689,0.004043525],"study_design_scores_gemma":[0.000008104264,0.00009288764,0.001082373,0.000007888344,0.000008626813,0.00005549638,0.00001048562,0.004059346,0.9921628,0.0001195128,0.002378321,0.00001424357],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5313408,0.004814531,0.4498798,0.0009830062,0.000486712,0.0009123235,0.003663434,0.00420765,0.003711766],"genre_scores_gemma":[0.577833,0.003271572,0.4117958,0.000517105,0.000147659,0.001073617,0.002161046,0.0002280211,0.002972137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001169545,"threshold_uncertainty_score":0.003940046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01410778940059756,"score_gpt":0.2726076726446685,"score_spread":0.2584998832440709,"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."}}