{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1307508,0.0009513207,0.001470012,0.001830044,0.002467076,0.002853911,0.002808617,0.001724039,0.02596177],"category_scores_gemma":[0.1346982,0.001058525,0.001376866,0.001908154,0.002238537,0.001936291,0.004434205,0.00354875,0.007968819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002523142,"about_ca_system_score_gemma":0.01125654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001647741,"about_ca_topic_score_gemma":0.002114546,"domain_scores_codex":[0.9284027,0.05476353,0.004011517,0.003057068,0.008322298,0.001442856],"domain_scores_gemma":[0.8179157,0.06741491,0.02038082,0.05691977,0.03057504,0.006793808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.03071976,0.00605903,0.02867933,0.00357371,0.0007630205,0.001553338,0.00879668,0.007310638,0.05538535,0.02435497,0.07027093,0.7625333],"study_design_scores_gemma":[0.01110428,0.05399802,0.08118726,0.002748614,0.001026782,0.001870276,0.005308561,0.01383007,0.1262952,0.0498661,0.6523045,0.0004602835],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.1710655,0.002123048,0.6154339,0.01427266,0.004104578,0.1037606,0.005886197,0.004426758,0.07892682],"genre_scores_gemma":[0.2564766,0.001057768,0.6370834,0.005308637,0.001573432,0.07144007,0.002874913,0.0008864118,0.02329881],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.1307508,"threshold_uncertainty_score":0.6914844,"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."}}