{"id":"W2917356760","doi":"10.1039/c9ay00192a","title":"Informatics analysis of capillary electropherograms of autologously doped and undoped blood","year":2019,"lang":"en","type":"article","venue":"Analytical Methods","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"World Anti-Doping Agency","keywords":"Electropherogram; Capillary electrophoresis; Chromatography; Doping; Capillary action; Chemistry; Computer science; Materials science; Optoelectronics","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":[0.0003779634,0.0001375065,0.0006086288,0.0002446282,0.00001685165,0.00000946357,0.0001453941,0.000111823,0.0001533161],"category_scores_gemma":[0.00003889318,0.0001221277,0.0001631522,0.00131825,0.00008694523,0.00004394423,0.00003461596,0.0001303459,0.000004460363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001386916,"about_ca_system_score_gemma":0.00002142088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002858633,"about_ca_topic_score_gemma":0.000002145975,"domain_scores_codex":[0.9989077,0.00007653217,0.0005460746,0.0001161772,0.0001315598,0.0002219005],"domain_scores_gemma":[0.9991583,0.0002424095,0.00008390813,0.0003632499,0.00007243142,0.00007965534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003622819,0.0001533634,0.01168893,0.0004426095,0.00878608,0.000001855236,0.0005122317,0.001658947,0.9279288,0.0303714,0.001074131,0.01734545],"study_design_scores_gemma":[0.0007946467,0.0004513593,0.01016913,0.00002510435,0.008309383,0.00001583614,0.0002839487,0.5029752,0.4686853,0.0009602388,0.006821549,0.0005082899],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9484383,0.007082488,0.04202408,0.00001708783,0.00001646702,0.0001492723,0.000006389031,0.00005229738,0.002213645],"genre_scores_gemma":[0.9575684,0.0130594,0.02921392,0.00003221809,0.000007973586,0.000007512769,0.00001980061,0.00001839707,0.0000723749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5013163,"threshold_uncertainty_score":0.4980223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008505518575841019,"score_gpt":0.2782323892631491,"score_spread":0.2697268706873081,"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."}}