{"id":"W2810946894","doi":"10.1080/10837450.2018.1492617","title":"Specificity of process analytical tools in the monitoring of multicomponent pharmaceutical powders","year":2018,"lang":"en","type":"article","venue":"Pharmaceutical Development and Technology","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Pfizer (Canada); Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Pfizer","keywords":"Process analytical technology; Active ingredient; Component (thermodynamics); Process engineering; Computer science; Biochemical engineering; Process (computing); Factorial experiment; Ascorbic acid; Work in process; Chemistry; Machine learning; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002322278,0.0001716685,0.0003532879,0.0003179413,0.00006625005,0.00001212158,0.0003787315,0.0001729889,0.0002769842],"category_scores_gemma":[0.0001823333,0.0001280287,0.00003750328,0.001031751,0.0008349027,0.00005667295,0.0001176443,0.0004041221,0.000005520049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004528834,"about_ca_system_score_gemma":0.00005438823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002078247,"about_ca_topic_score_gemma":8.310581e-7,"domain_scores_codex":[0.998552,0.00001798216,0.0004960219,0.000287,0.0002873618,0.000359601],"domain_scores_gemma":[0.9993749,0.0001813388,0.00009132986,0.0001719936,0.0001108903,0.00006957504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002662469,0.001689708,0.7023825,0.0005936766,0.000371211,0.00003548583,0.00131659,0.000001562687,0.2191849,0.009046095,0.00002983493,0.06508212],"study_design_scores_gemma":[0.0007435826,0.00003284877,0.008087165,0.00003631928,0.00009711184,0.00001341161,0.001502629,0.0006757795,0.9864591,0.0003174588,0.001886119,0.0001484973],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960918,0.0005370088,0.000110311,0.000658494,0.00003508206,0.00008492957,0.000002765302,0.00004222345,0.002437402],"genre_scores_gemma":[0.9988739,0.0001440017,0.0008539965,0.00002693599,0.00004939235,0.00001802843,0.000002353151,0.000008997793,0.00002236078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7672741,"threshold_uncertainty_score":0.5220859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09417254451777804,"score_gpt":0.3940318824635554,"score_spread":0.2998593379457773,"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."}}