{"id":"W1976195428","doi":"10.1002/rcm.2013","title":"A strategy for identification of drug metabolites from dried blood spots using triple‐quadrupole/linear ion trap hybrid mass spectrometry","year":2005,"lang":"en","type":"article","venue":"Rapid Communications in Mass Spectrometry","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Merck Canada Inc. (Canada); TransCanada (Canada)","funders":"","keywords":"Chemistry; Quadrupole ion trap; Chromatography; Triple quadrupole mass spectrometer; Mass spectrometry; Ion trap; Dried blood; Quadrupole; Analytical Chemistry (journal); Selected reaction monitoring; Tandem mass spectrometry; Atomic physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001176995,0.0006085029,0.001043264,0.001544626,0.0004106348,0.0001498462,0.002827319,0.0002934406,0.00221768],"category_scores_gemma":[0.0002693978,0.0007207652,0.0005250263,0.002718536,0.0003498136,0.0004861696,0.000257212,0.0009619939,0.00001854195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000541222,"about_ca_system_score_gemma":0.0001990988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002725771,"about_ca_topic_score_gemma":0.00005297024,"domain_scores_codex":[0.9951406,0.0002041916,0.002196581,0.0009965758,0.0006198616,0.0008421874],"domain_scores_gemma":[0.9928928,0.0008625154,0.001251655,0.004503909,0.0002882348,0.0002008822],"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":[0.00007112958,0.001217504,0.002202519,0.0001137172,0.0002672931,0.000001247687,0.0001194691,0.0002326688,0.9607043,0.03282443,0.0000886651,0.002157049],"study_design_scores_gemma":[0.001924995,0.00005671283,0.001874531,0.00009846771,0.0004032029,0.00001399175,0.0006215213,0.03089331,0.9262217,0.03508692,0.00208106,0.000723545],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9037964,0.009144059,0.07187121,0.001496039,0.0001142568,0.001451913,0.001904001,0.0006120452,0.009610089],"genre_scores_gemma":[0.7081564,0.002169229,0.2878256,0.00002662915,0.0002844723,0.0003554058,0.0007731926,0.00009810069,0.0003110156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2159543,"threshold_uncertainty_score":0.9995244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03377006634405858,"score_gpt":0.3122589423342313,"score_spread":0.2784888759901727,"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."}}