{"id":"W2032701435","doi":"10.1016/j.jchromb.2005.08.008","title":"Determination of atorvastatin in human serum by reversed-phase high-performance liquid chromatography with UV detection","year":2005,"lang":"en","type":"article","venue":"Journal of Chromatography B","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":107,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of Alberta","keywords":"Chromatography; Chemistry; Atorvastatin; Calibration curve; Bioequivalence; Detection limit; Diclofenac Sodium; High-performance liquid chromatography; Extraction (chemistry); Absorbance; Quantitative analysis (chemistry); Standard curve; Methanol; Pharmacokinetics; Pharmacology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009756536,0.0002323692,0.000433745,0.001387563,0.00009944459,0.00006846389,0.0006229451,0.00008202711,0.00001127592],"category_scores_gemma":[0.00002227253,0.000207498,0.0001927212,0.001962074,0.0001466418,0.001966911,0.00006204374,0.0002803787,0.000001216371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007805324,"about_ca_system_score_gemma":0.0001146793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001692425,"about_ca_topic_score_gemma":0.00002363209,"domain_scores_codex":[0.997448,0.0002452372,0.0009828625,0.0002657298,0.0007769469,0.0002811768],"domain_scores_gemma":[0.9979661,0.0001535711,0.001132086,0.0003088949,0.0003177547,0.0001216609],"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":[0.001775368,0.005220973,0.03367752,0.0008969754,0.0005595186,0.0002198742,0.005697115,0.03760668,0.4874522,0.004377278,0.001026392,0.4214901],"study_design_scores_gemma":[0.009732991,0.007792029,0.1066308,0.0009808311,0.000086587,0.0007182465,0.0001729258,0.07262404,0.7981103,0.001357007,0.000948225,0.0008460401],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7618913,0.0001456817,0.2375176,0.0001049561,0.0001186355,0.000128619,0.000006012614,0.00002767235,0.00005954913],"genre_scores_gemma":[0.9141362,0.00004199386,0.08566747,0.00005876538,0.00006746918,0.000006286717,0.000002182623,0.00001722735,0.000002457943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.420644,"threshold_uncertainty_score":0.8461521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00817345608127069,"score_gpt":0.2732466648707203,"score_spread":0.2650732087894496,"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."}}