{"id":"W7117793145","doi":"10.2139/ssrn.5995512","title":"Development and validation of an LC-MS/MS/MS (MRM³) method for the sensitive quantification of trace β -agonists in complex animal-derived food matrices","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Pharmacological Effects and Assays","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Matrix (chemical analysis); Sensitivity (control systems); Analyte; Linearity; Tandem mass spectrometry; Detection limit; Complex matrix; Mass spectrometry","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":[0.002762459,0.001480866,0.000817581,0.001339292,0.000980478,0.001131675,0.001271266,0.002286683,0.001802517],"category_scores_gemma":[0.00228208,0.0009510852,0.0009828948,0.0005475382,0.001177686,0.0008864407,0.00131114,0.001731933,0.002377761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009079385,"about_ca_system_score_gemma":0.002595568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001599569,"about_ca_topic_score_gemma":0.003832493,"domain_scores_codex":[0.9971253,0.0003430448,0.0001749852,0.0007394062,0.001467662,0.0001495678],"domain_scores_gemma":[0.998594,0.0003074917,0.0002112967,0.000153955,0.0006004639,0.0001328514],"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":[0.0001653318,0.00005783621,0.0003277063,0.0002443726,0.0000518655,0.00007575929,0.00005483373,0.0002084839,0.9852873,0.0002784708,0.0002828302,0.01296515],"study_design_scores_gemma":[0.00003617356,0.0007063276,0.001660361,0.0000545742,0.00008906263,0.0009432096,0.00003686599,0.002857869,0.9840809,0.0003039336,0.009171102,0.00005962618],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2627804,0.01497726,0.7011741,0.001240821,0.001013989,0.002725123,0.004397688,0.003994117,0.007696598],"genre_scores_gemma":[0.3644998,0.008206138,0.6029825,0.002088732,0.0002508968,0.003041026,0.003437168,0.000420678,0.01507316],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002762459,"threshold_uncertainty_score":0.0146094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05354429582039451,"score_gpt":0.3330937575822117,"score_spread":0.2795494617618172,"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."}}