{"id":"W4410167559","doi":"10.1002/smtd.202500658","title":"Native Taylor/Non‐Taylor Dispersion–Mass Spectrometry (TNT‐MS) Allows Rapid Protein Desalting and Multiplexed, Label‐Free Ligand Screening","year":2025,"lang":"en","type":"article","venue":"Small Methods","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Structural Genomics Consortium; Genentech; Deutsche Krebshilfe; Bundesministerium für Bildung und Forschung; Technische Universität Darmstadt; Ontario Genomics Institute; Hessisches Ministerium für Wissenschaft und Kunst; Fonds der Chemischen Industrie; Ontario Genomics; Genome Canada; Bayer; Alexander von Humboldt-Stiftung; Deutsche Forschungsgemeinschaft; Bristol-Myers Squibb","keywords":"Mass spectrometry; Taylor dispersion; Chemistry; Analyte; Electrospray ionization; Chromatography; Small molecule; Electrospray; Elution; Ligand (biochemistry); Dispersion (optics); Analytical Chemistry (journal); Capillary action; Materials science; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008593865,0.0006740357,0.0004916223,0.000603019,0.000378938,0.000731875,0.0004078003,0.0006063923,0.0008654078],"category_scores_gemma":[0.000704915,0.0002751545,0.0003299765,0.0003243873,0.0007246662,0.0007673816,0.000666391,0.0008853189,0.0006209447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004981293,"about_ca_system_score_gemma":0.0005211505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005904121,"about_ca_topic_score_gemma":0.001150975,"domain_scores_codex":[0.9994004,0.00007833183,0.0000277225,0.0001940842,0.0002391333,0.00006028278],"domain_scores_gemma":[0.9996414,0.0001169101,0.00009115205,0.00004406598,0.0000718587,0.0000345588],"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":[0.00004049285,0.00001974893,0.000189833,0.00005696983,0.000006587823,0.00003175276,0.00002518982,0.000101224,0.9917778,0.0003702637,0.0001346711,0.007245489],"study_design_scores_gemma":[0.000004375052,0.00008454422,0.0005840217,0.000004857979,0.00000680086,0.0001463036,0.00001429666,0.002698693,0.9938316,0.000187864,0.002425418,0.00001124996],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6341915,0.009712465,0.3430078,0.0006306021,0.0002711348,0.0004199264,0.001218744,0.003475553,0.007072208],"genre_scores_gemma":[0.7351868,0.008007485,0.2469323,0.000442348,0.0001485901,0.0003492713,0.001115151,0.0003485888,0.007469491],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0008654078,"threshold_uncertainty_score":0.004544914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02993411853757507,"score_gpt":0.3320257871250876,"score_spread":0.3020916685875126,"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."}}