{"id":"W4408411802","doi":"10.3390/pharmaceutics17030364","title":"Experimental and Numerical Study to Enhance Granule Control and Quality Predictions in Pharmaceutical Granulations","year":2025,"lang":"en","type":"article","venue":"Pharmaceutics","topic":"Granular flow and fluidized beds","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Université de Lyon","keywords":"Granulation; Granule (geology); Critical quality attributes; Process engineering; Impeller; Materials science; Biological system; Agglomerate; Quality by Design; Computer science; Mechanical engineering; Particle size; Engineering; Composite material; Chemical 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":[],"consensus_categories":[],"category_scores_codex":[0.0002604678,0.0001713092,0.000240463,0.000158497,0.0001071411,0.00004221412,0.00007938018,0.00004214168,0.00001878646],"category_scores_gemma":[0.0000258476,0.0001862259,0.00002856322,0.0003482219,0.00005260268,0.00009240336,0.0000525767,0.0002553001,0.000006431874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005838865,"about_ca_system_score_gemma":0.00001201394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002407039,"about_ca_topic_score_gemma":0.000007988284,"domain_scores_codex":[0.9989323,0.0001021717,0.0003190795,0.0002447828,0.0001353391,0.0002663095],"domain_scores_gemma":[0.9995334,0.0001206776,0.00001038407,0.0001361383,0.00002237798,0.0001770399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003954571,0.002270228,0.2981123,0.0002222587,0.0003351123,0.00002632313,0.006661064,0.00449645,0.6735485,0.002133297,0.0008891518,0.01090985],"study_design_scores_gemma":[0.01149693,0.0002244182,0.131339,0.00007040983,0.0003744822,0.00001212319,0.001821117,0.5876627,0.2450208,0.0002042711,0.02083494,0.0009387821],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9318976,0.002174133,0.06373163,0.0002731486,0.0003544205,0.0007986687,0.00003477999,0.0001832791,0.0005523717],"genre_scores_gemma":[0.999206,0.00004386789,0.0002424073,0.0003376282,0.00003446372,0.00009378498,0.000003340515,0.00001610263,0.00002240614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5831662,"threshold_uncertainty_score":0.7594071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0301312870935824,"score_gpt":0.3823258511174509,"score_spread":0.3521945640238685,"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."}}