{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007136912,0.0003652324,0.0004001048,0.0002945609,0.0003258453,0.0004639943,0.0005530216,0.0007370959,0.001638163],"category_scores_gemma":[0.001534167,0.0001370642,0.0003013357,0.0003261166,0.000447424,0.0003671257,0.0003095138,0.0004634534,0.0001562552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003631276,"about_ca_system_score_gemma":0.0002816608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001560814,"about_ca_topic_score_gemma":0.001116829,"domain_scores_codex":[0.9997581,0.00004253134,0.00002718281,0.00004952295,0.0001032189,0.000019486],"domain_scores_gemma":[0.999032,0.00047385,0.000102448,0.0001644968,0.0001974125,0.00002974779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005372798,0.0006454999,0.009903038,0.0005852225,0.0000303512,0.0003514657,0.0001892276,0.754652,0.1968866,0.003308889,0.0006265697,0.03228382],"study_design_scores_gemma":[0.00002647016,0.0001478692,0.001492615,0.000008934399,0.000007824841,0.00003409033,0.00002017305,0.9350934,0.06226669,0.0003264618,0.0005666693,0.000008757383],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8371444,0.0003971879,0.1544116,0.0001986914,0.000085533,0.0001887147,0.0004938546,0.0005189031,0.006561146],"genre_scores_gemma":[0.968514,0.00009353869,0.03074227,0.00001547931,0.000005801066,0.00005753153,0.0001431832,0.00001467207,0.0004134929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001638163,"threshold_uncertainty_score":0.00548023,"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."}}