{"id":"W2067306560","doi":"10.1002/qaj.294","title":"Conducting portions of GLP studies in GMP laboratories","year":2004,"lang":"en","type":"article","venue":"The Quality Assurance Journal","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Eli Lilly (Canada); Purdue Pharma (Canada)","funders":"","keywords":"Good laboratory practice; Good manufacturing practice; Clinical Practice; Overhead (engineering); Risk analysis (engineering); Engineering; Computer science; Engineering ethics; Management science; Medicine; Operations management; Nursing; Electrical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01956089,0.0001186453,0.0007017168,0.00004270875,0.0001693423,0.00002593591,0.0002730761,0.00007016289,0.00004098154],"category_scores_gemma":[0.2421179,0.00007486825,0.000110199,0.0004108084,0.000432578,0.0001252239,0.00005014079,0.0006075302,0.000004415573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009131262,"about_ca_system_score_gemma":0.0001802824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002263417,"about_ca_topic_score_gemma":0.0000682089,"domain_scores_codex":[0.9953523,0.002003141,0.001799822,0.000129759,0.0004835262,0.0002314639],"domain_scores_gemma":[0.9465381,0.05088864,0.001415474,0.0003997243,0.0006830373,0.00007504767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002075875,0.0004956443,0.006581314,0.0005312303,0.0004128626,0.00004325749,0.01063609,0.0003603555,0.003382832,0.9738011,0.0008167669,0.002731],"study_design_scores_gemma":[0.0008911785,0.00005116667,0.003794653,0.0003547402,0.00004010289,0.00002776708,0.006090126,0.000001423319,0.0033188,0.9852965,0.0000409067,0.00009262877],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9495189,0.0007423069,0.0417423,0.005704646,0.001502315,0.0002456057,0.00005214802,0.00003039544,0.0004613852],"genre_scores_gemma":[0.6866222,0.0002065927,0.3127058,0.00010341,0.0003163032,0.000006292544,7.430178e-8,0.00001101589,0.00002828423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2709635,"threshold_uncertainty_score":0.7642661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.89577125109756,"score_gpt":0.6918572440235644,"score_spread":0.2039140070739955,"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."}}