{"id":"W2405920067","doi":"10.1007/s00216-016-9614-9","title":"Quantification of 11 thyroid hormones and associated metabolites in blood using isotope-dilution liquid chromatography tandem mass spectrometry","year":2016,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Thyroid Disorders and Treatments","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Isotope dilution; Chromatography; Chemistry; Mass spectrometry; Tandem mass spectrometry; Liquid chromatography–mass spectrometry; Metabolomics; Thyroid hormones; Hormone; Biochemistry","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":[0.0008888999,0.0005836792,0.0005488853,0.0008477346,0.0006296356,0.0007559929,0.0005237218,0.0009390769,0.0006415023],"category_scores_gemma":[0.00128753,0.0003472804,0.0003401427,0.0007240777,0.0006203029,0.0004209508,0.0003152529,0.0007533984,0.0003616331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006405987,"about_ca_system_score_gemma":0.001271212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002462566,"about_ca_topic_score_gemma":0.005013649,"domain_scores_codex":[0.9990073,0.0002169479,0.00005531603,0.0002502762,0.0003984241,0.00007177868],"domain_scores_gemma":[0.9996194,0.0001160641,0.00006185486,0.00002868888,0.0001165883,0.00005747122],"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":[0.003338348,0.0004229464,0.04672612,0.000235759,0.0003492762,0.0003798326,0.0001817215,0.0006005118,0.8908478,0.0003984503,0.001003211,0.05551608],"study_design_scores_gemma":[0.0002355873,0.002098274,0.09989741,0.00005828916,0.0004300261,0.003416766,0.000153273,0.008693164,0.8767858,0.0005858747,0.007537734,0.0001077992],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9221669,0.01847276,0.05054947,0.0006397188,0.0002991544,0.0003271409,0.001858664,0.0007865086,0.004899747],"genre_scores_gemma":[0.929853,0.005006568,0.057097,0.001907704,0.0001384898,0.0003408872,0.001378024,0.00007400661,0.00420429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002462566,"threshold_uncertainty_score":0.004896462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01531790435730858,"score_gpt":0.2573858849644714,"score_spread":0.2420679806071628,"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."}}