{"id":"W4416354649","doi":"10.1039/d5an01073j","title":"Computational and design of experiment strategies to improve differentiation and quantitation of trace-level cannabinoids by copper cationization paper spray mass spectrometry","year":2025,"lang":"en","type":"article","venue":"The Analyst","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Island University; University of Victoria","funders":"British Columbia Knowledge Development Fund; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Mass spectrometry; Copper; Tandem mass spectrometry; Isobaric process; Ion-mobility spectrometry; Electrospray; Electrospray ionization; Analytical Chemistry (journal)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001319588,0.00009615286,0.0001552822,0.0001189972,0.00008428103,0.00004177779,0.00009230235,0.00004928584,0.0001248277],"category_scores_gemma":[0.00001959474,0.00007969679,0.00002404849,0.0003655325,0.00006084874,0.00009140422,0.00002445527,0.00005347235,3.372488e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004373394,"about_ca_system_score_gemma":0.00004480755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001827114,"about_ca_topic_score_gemma":0.00001014799,"domain_scores_codex":[0.99929,0.0000271816,0.0002803295,0.0001733937,0.0001467264,0.0000823587],"domain_scores_gemma":[0.9994347,0.00008693435,0.0001507559,0.0001736434,0.0001289614,0.00002498442],"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":[0.00002084549,0.00005912743,0.001242187,0.00006633238,0.0000710606,2.734007e-8,0.0003343461,0.0009091931,0.9436135,0.0526993,0.0005608614,0.0004231973],"study_design_scores_gemma":[0.0004608491,0.00009111911,0.01526641,0.00005241971,0.0001850858,7.82402e-7,0.002562467,0.01428699,0.9505856,0.01614901,0.0001759109,0.0001833746],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3303443,0.0004147747,0.6666296,0.001149097,0.000008853768,0.0002202,0.00007070503,0.00002266619,0.001139706],"genre_scores_gemma":[0.9875752,0.00005149754,0.01191607,0.00002942081,0.000009134821,0.00004241699,0.00007580458,0.000006792656,0.0002936873],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6572308,"threshold_uncertainty_score":0.3249941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0136687093013573,"score_gpt":0.2769185352980974,"score_spread":0.2632498259967401,"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."}}