{"id":"W4407938817","doi":"10.1021/acs.analchem.4c06350","title":"Multilevel─Intact, Subunits, and Peptides─Characterization of Antibody-Based Therapeutics by a Single-Column LC–MS Setup","year":2025,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"Biomedical Research Council","keywords":"Chemistry; Chromatography; Column (typography); Characterization (materials science); Nanotechnology","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":[0.001137133,0.001827519,0.0009050472,0.001319102,0.0008165591,0.001192117,0.001469476,0.001111303,0.005585819],"category_scores_gemma":[0.0009902201,0.0006875176,0.000712755,0.0005219539,0.0007313612,0.001108903,0.001282865,0.001743102,0.003639379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007764073,"about_ca_system_score_gemma":0.001465813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001110103,"about_ca_topic_score_gemma":0.001852993,"domain_scores_codex":[0.9982796,0.0001494744,0.0001283612,0.0005476955,0.0007389244,0.000155985],"domain_scores_gemma":[0.9994318,0.000162362,0.00008901811,0.00009287854,0.0001591868,0.0000647948],"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":[0.000201442,0.00007168989,0.000489242,0.0001075962,0.00003377789,0.00005937902,0.00003092927,0.0001630271,0.9879791,0.0003173083,0.0004917326,0.01005486],"study_design_scores_gemma":[0.00003240431,0.0003795723,0.002512519,0.00002519289,0.00005415121,0.0003558105,0.00003930057,0.006807927,0.9819857,0.0003767337,0.007363943,0.00006675129],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4063679,0.003249526,0.5594277,0.0006603652,0.0004482317,0.002574439,0.005428427,0.01199489,0.009848556],"genre_scores_gemma":[0.332547,0.002545963,0.6426812,0.001903663,0.0002022856,0.003262277,0.006827582,0.00109866,0.008931291],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005585819,"threshold_uncertainty_score":0.01868641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01347654374482703,"score_gpt":0.2795134200852999,"score_spread":0.2660368763404728,"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."}}