{"id":"W6950631775","doi":"10.5683/sp3/yfgxdz","title":"Replication Data for: \"Analysis of Trimethyl Silyl Derivatives of Creatinine in Human Urine by GC×GC-TOFMS and Multiway Decomposition\"","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Silylation; Creatinine; Replication (statistics); Urine; Dimension (graph theory)","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":[0.00263543,0.003768633,0.002253231,0.002740849,0.001223802,0.002155676,0.004105186,0.003192334,0.0426576],"category_scores_gemma":[0.008002767,0.0007412523,0.002398842,0.00403538,0.0007715307,0.00103483,0.001860972,0.001954152,0.06201754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00155939,"about_ca_system_score_gemma":0.003600546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03453657,"about_ca_topic_score_gemma":0.06715421,"domain_scores_codex":[0.9978393,0.0003839812,0.0002567348,0.0008450193,0.0004368765,0.0002381909],"domain_scores_gemma":[0.9965374,0.000822832,0.0003306273,0.001114828,0.0009422913,0.0002520274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003893302,0.00007716215,0.00233255,0.00173559,0.0001989043,0.0000775107,0.00003875311,0.0006825474,0.0008183729,0.000335873,0.9883658,0.004947758],"study_design_scores_gemma":[0.001126448,0.0000969442,0.01323393,0.0004999877,0.0002851969,0.0001874564,0.0001165357,0.001033386,0.00224329,0.001770661,0.979291,0.0001151684],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003297418,0.0001047958,0.0001488775,0.00005794767,0.00004575199,0.00001791303,0.9984447,0.0005124331,0.0003378387],"genre_scores_gemma":[0.0005388638,0.00003492752,0.0003987522,0.00003474748,0.000006305726,0.0000687815,0.9985297,0.00005524162,0.0003326493],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0426576,"threshold_uncertainty_score":0.1427038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05382342610871608,"score_gpt":0.3828554524791987,"score_spread":0.3290320263704826,"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."}}