{"id":"W3164373175","doi":"10.1093/clinchem/hvab074","title":"Broadening the Horizon of Antidoping Analytical Approaches Using Dried Blood Spots","year":2021,"lang":"en","type":"letter","venue":"Clinical Chemistry","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"World Anti-Doping Agency","keywords":"Dried blood; Spots; Chromatography; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01185384,0.0008431833,0.001083109,0.0008774842,0.001790775,0.00468011,0.001993513,0.03491532,0.003610727],"category_scores_gemma":[0.02927043,0.0006146161,0.001312298,0.0004654943,0.006350041,0.006609228,0.00203863,0.03591615,0.003579913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003773563,"about_ca_system_score_gemma":0.002710865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001656634,"about_ca_topic_score_gemma":0.00315112,"domain_scores_codex":[0.9908047,0.002897124,0.0006779035,0.0009660806,0.004129031,0.000525268],"domain_scores_gemma":[0.9743773,0.01831079,0.001031264,0.0007634379,0.003607367,0.001909872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002674717,0.0001664148,0.0009507571,0.000268367,0.00004675713,0.003586845,0.0004055593,0.0002409865,0.002558549,0.0366172,0.8347548,0.1201362],"study_design_scores_gemma":[0.000217262,0.0002138435,0.0007693417,0.0003366373,0.00003408261,0.00404028,0.0002658548,0.001176741,0.001820073,0.04954185,0.9415145,0.00006939808],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0008177116,0.009436245,0.0025114,0.9649464,0.01799171,0.00001986933,0.00001967314,0.00006760699,0.004189409],"genre_scores_gemma":[0.01359655,0.008530485,0.003192037,0.8864386,0.08137825,0.00005095099,0.00002569106,0.00005458528,0.006732814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03491532,"threshold_uncertainty_score":0.06268978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2198762732898227,"score_gpt":0.3683143893273673,"score_spread":0.1484381160375446,"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."}}