{"id":"W2107027175","doi":"10.1016/j.jchromb.2011.05.027","title":"Analyte and internal standard cross signal contributions and their impact on quantitation in LC–MS based bioanalysis","year":2011,"lang":"en","type":"article","venue":"Journal of Chromatography B","topic":"Pesticide Residue Analysis and Safety","field":"Agricultural and Biological Sciences","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"BioPhage Pharma (Canada)","funders":"","keywords":"Analyte; Bioanalysis; Chemistry; Calibration; Linearity; Chromatography; Weighting; SIGNAL (programming language); Accuracy and precision; Calibration curve; Analytical Chemistry (journal); Range (aeronautics); Biological system; Detection limit; Statistics; Computer science; Mathematics; Materials science","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":[0.009989415,0.001320986,0.0005815768,0.001602959,0.001260528,0.001849631,0.0009654182,0.002456268,0.002242742],"category_scores_gemma":[0.01499872,0.001464155,0.0008315456,0.001052714,0.001468515,0.001070456,0.001237567,0.001441458,0.0008209394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001259229,"about_ca_system_score_gemma":0.000983395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001193883,"about_ca_topic_score_gemma":0.002466725,"domain_scores_codex":[0.9916642,0.003287155,0.0003832827,0.00146742,0.002830328,0.0003676872],"domain_scores_gemma":[0.9888859,0.008218789,0.0006185306,0.000643788,0.00138644,0.0002465517],"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":[0.002011659,0.0003025135,0.00693147,0.0003283054,0.0003219396,0.0007238297,0.0004301236,0.003175381,0.9413155,0.002456768,0.0007621971,0.0412403],"study_design_scores_gemma":[0.0000372225,0.000378092,0.008537345,0.0000513916,0.0002489694,0.001248608,0.00006301785,0.01919606,0.9665675,0.0007375622,0.002893735,0.00004047198],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.775372,0.01578899,0.1971152,0.0009551605,0.0006922826,0.0003631678,0.0003738403,0.001284153,0.008055161],"genre_scores_gemma":[0.915103,0.003633529,0.07253274,0.001362778,0.0001798848,0.0003744775,0.0007007981,0.0004975069,0.005615251],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.009989415,"threshold_uncertainty_score":0.05282968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01583015498012064,"score_gpt":0.2673269210731827,"score_spread":0.251496766093062,"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."}}