{"id":"W4285509048","doi":"10.18609/cgti.2021.219","title":"Process development and scale-up of pluripotent stem cell manufacturing","year":2021,"lang":"en","type":"article","venue":"Cell and Gene Therapy Insights","topic":"Pluripotent Stem Cells Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Induced pluripotent stem cell; Process (computing); Process development; Scale (ratio); Manufacturing process; Manufacturing engineering; Computer science; Engineering; Biology; Materials science; Geography; Embryonic stem cell; Operating system; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008308815,0.0001667553,0.0001739131,0.000041602,0.0001098033,0.00002376495,0.0001090568,0.000108046,0.00001169781],"category_scores_gemma":[7.446862e-7,0.0001383663,0.00003652745,0.00004949001,0.00006896064,0.000004738525,0.0001176192,0.00007564556,0.000003030409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007330333,"about_ca_system_score_gemma":0.0001155556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003033695,"about_ca_topic_score_gemma":0.000009429989,"domain_scores_codex":[0.9989437,0.00005564639,0.000206731,0.000396823,0.0001803812,0.0002166561],"domain_scores_gemma":[0.9994977,0.000008392056,0.0000643048,0.0002188438,0.00009108859,0.0001197263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009509368,0.00008909531,0.0002071759,0.0001637743,0.00003219598,0.00001279717,0.0009926021,0.00001848737,0.9823405,8.138919e-7,0.0000300343,0.01601748],"study_design_scores_gemma":[0.000998124,0.0001177994,0.0008849271,0.00001495997,0.000005299994,0.00001598434,0.0002773705,0.00001497208,0.9806247,0.0000254854,0.01684438,0.0001760266],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9788702,0.01973262,0.0001270107,0.00002833793,0.00006891261,0.0001550238,0.000003525918,0.000006071585,0.001008319],"genre_scores_gemma":[0.9890292,0.006438752,0.0003887837,0.00007111534,0.00005049443,0.00001335697,0.00003717043,0.00001913742,0.003951967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01681434,"threshold_uncertainty_score":0.5642413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01458430121772456,"score_gpt":0.2334971514675452,"score_spread":0.2189128502498206,"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."}}