{"id":"W4402170938","doi":"10.1093/jalm/jfae050","title":"Proficiency Testing Customization in Clinical Trials: How the pSMILE Project Ensures High-Quality Proficiency Testing Coverage for International Laboratories","year":2024,"lang":"en","type":"article","venue":"The Journal of Applied Laboratory Medicine","topic":"Clinical Laboratory Practices and Quality Control","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Allergy and Infectious Diseases; National Institutes of Health","keywords":"Quality (philosophy); Personalization; Test (biology); Reliability engineering; Medical physics; Computer science; Medicine; Engineering; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4582353,0.002759262,0.002067681,0.007472754,0.004234402,0.02758243,0.01278292,0.007611313,0.01354848],"category_scores_gemma":[0.5050866,0.003250665,0.002118563,0.004484051,0.008765231,0.02241389,0.02870861,0.01335465,0.01561184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008304383,"about_ca_system_score_gemma":0.06666427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005925542,"about_ca_topic_score_gemma":0.007271085,"domain_scores_codex":[0.5449733,0.3255481,0.02498311,0.01657483,0.07831567,0.009605153],"domain_scores_gemma":[0.4444228,0.202872,0.03595636,0.1180535,0.1554181,0.04327725],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004444162,0.0009707747,0.01262696,0.001661544,0.0002366784,0.0007150947,0.005971557,0.004146553,0.002147881,0.02635454,0.2704529,0.6742711],"study_design_scores_gemma":[0.000406291,0.002328686,0.01233433,0.008285397,0.000188956,0.001983815,0.003491984,0.00917777,0.006033313,0.06031829,0.8950116,0.0004395962],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01583473,0.008909528,0.5503404,0.2852665,0.007410142,0.01828704,0.001824179,0.02739499,0.08473264],"genre_scores_gemma":[0.07228503,0.00530193,0.8448957,0.04305299,0.003144566,0.008367646,0.002531258,0.005945447,0.01447545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5417647,"threshold_uncertainty_score":0.6680924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2966461972733409,"score_gpt":0.5039288514970655,"score_spread":0.2072826542237245,"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."}}