{"id":"W2991547990","doi":"10.1002/pst.1984","title":"Comparisons of outlier tests for potency bioassays","year":2019,"lang":"en","type":"article","venue":"Pharmaceutical Statistics","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"AstraZeneca (Canada)","funders":"","keywords":"Potency; Outlier; Bioassay; Statistics; Mathematics; Computer science; Chemistry; Biology","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":[0.04783844,0.001451817,0.001643336,0.003985893,0.0008886352,0.002177445,0.002626708,0.001738965,0.001920667],"category_scores_gemma":[0.192626,0.0003889211,0.002231824,0.002981519,0.001701781,0.002745697,0.002430146,0.002582336,0.0005080342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001816957,"about_ca_system_score_gemma":0.002025345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001987203,"about_ca_topic_score_gemma":0.001724228,"domain_scores_codex":[0.9459803,0.03128923,0.004382425,0.003779097,0.01340628,0.001162658],"domain_scores_gemma":[0.6897569,0.2608133,0.01158022,0.01546481,0.02108192,0.001302795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005935668,0.001062856,0.05648752,0.001778632,0.001595239,0.0006665157,0.0008862521,0.4131902,0.01610249,0.05401867,0.006422188,0.4418539],"study_design_scores_gemma":[0.0002691101,0.004485891,0.01732392,0.0001848882,0.0003486571,0.0006502005,0.0004614516,0.9125084,0.03414293,0.02290831,0.00648943,0.0002268307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1442031,0.002571831,0.8447823,0.0005045683,0.0004438613,0.0007470175,0.0008933133,0.001625779,0.004228129],"genre_scores_gemma":[0.6439056,0.001114755,0.3495632,0.0003012451,0.000187474,0.000772052,0.002652989,0.0003133831,0.001189331],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04783844,"threshold_uncertainty_score":0.2529969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2950893604694196,"score_gpt":0.5342374065051462,"score_spread":0.2391480460357266,"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."}}