{"id":"W2076359403","doi":"10.1002/biot.201300385","title":"Hybrid modeling for quality by design and PAT‐benefits and challenges of applications in biopharmaceutical industry","year":2014,"lang":"en","type":"article","venue":"Biotechnology Journal","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"GlaxoSmithKline (Canada)","funders":"","keywords":"Biopharmaceutical; Process (computing); Computer science; Quality (philosophy); Parametric statistics; Management science; Risk analysis (engineering); Quality by Design; Systems engineering; Biochemical engineering; Engineering; Business; Biotechnology; Operations management","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":[0.00564577,0.0008416782,0.000980599,0.0008941108,0.0003468458,0.003010466,0.001176606,0.001207061,0.001818043],"category_scores_gemma":[0.005760373,0.0004827337,0.001245601,0.0008613827,0.001181048,0.002442211,0.001681687,0.001404955,0.000400664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001694573,"about_ca_system_score_gemma":0.001510721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001832304,"about_ca_topic_score_gemma":0.001380556,"domain_scores_codex":[0.9971713,0.001434641,0.0001061808,0.0003066577,0.0008826644,0.00009860229],"domain_scores_gemma":[0.9966884,0.00216676,0.0003526917,0.0003159934,0.0004210633,0.0000550727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001425051,0.0001010394,0.002511431,0.0005033914,0.0001864575,0.000105232,0.0002281656,0.6226195,0.005804332,0.2133446,0.001992717,0.1524606],"study_design_scores_gemma":[0.0000128998,0.0001303814,0.0005998801,0.00008765374,0.00004607096,0.00005563784,0.00006293821,0.8910587,0.001636156,0.09781842,0.008467075,0.00002410505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00624536,0.0008168966,0.9894265,0.000744154,0.00002310951,0.00003806151,0.0000490599,0.0002215118,0.002435326],"genre_scores_gemma":[0.6847306,0.002215389,0.3086791,0.0003997025,0.00009869874,0.0002942296,0.0001861045,0.0001389497,0.003257188],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00564577,"threshold_uncertainty_score":0.02985805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05422969145828586,"score_gpt":0.2863576070288843,"score_spread":0.2321279155705984,"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."}}