{"id":"W3008506219","doi":"10.3390/mi11030235","title":"Surface Response Based Modeling of Liposome Characteristics in a Periodic Disturbance Mixer","year":2020,"lang":"en","type":"article","venue":"Micromachines","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Concordia University; École de Technologie Supérieure","funders":"Universitat Politècnica de Catalunya; McGill University Health Centre; Natural Sciences and Engineering Research Council of Canada; Université du Québec à Montréal; CMC Microsystems; Concordia University; École de technologie supérieure; Khalifa University of Science, Technology and Research; McGill University","keywords":"Liposome; Zeta potential; Dispersity; Biological system; Particle size; Volumetric flow rate; Vesicle; Micromixer; Response surface methodology; Materials science; Nanotechnology; Nanoparticle; Chemistry; Chromatography; Mechanics; Microfluidics; Membrane; Physics","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":[0.0001205341,0.0001693716,0.000290552,0.00006065009,0.00002587711,0.0000177983,0.0001859075,0.0001010205,0.000009869505],"category_scores_gemma":[0.0001223373,0.0001563093,0.00005308385,0.0002449892,0.00005972017,0.00004196405,0.00004651588,0.0001778541,0.000009985319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002862908,"about_ca_system_score_gemma":0.00002156929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002713824,"about_ca_topic_score_gemma":0.000003254625,"domain_scores_codex":[0.9992273,0.00003354932,0.000299909,0.0001744335,0.00007473423,0.0001901025],"domain_scores_gemma":[0.999669,0.00004736097,0.00003336674,0.000190495,0.00002417576,0.00003565809],"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":[0.0001676547,0.0000178472,0.007234147,0.0001317602,0.000007289903,0.00001851275,0.0003838168,0.004889533,0.986424,0.000003594692,0.0003239417,0.0003978474],"study_design_scores_gemma":[0.000451454,0.00005807693,0.007330749,0.0001278516,0.00001126262,0.000005098148,0.00007778648,0.7980354,0.1924227,0.00001599549,0.001174117,0.0002894639],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912648,0.002137695,0.005259628,0.0007153181,0.000080721,0.00009137354,0.00006223786,0.0003701967,0.00001801459],"genre_scores_gemma":[0.9967953,0.00008138218,0.002957114,0.00009150662,0.00002171211,0.000001430135,0.00001253782,0.00002794374,0.00001106311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7940013,"threshold_uncertainty_score":0.6374107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01556656046030645,"score_gpt":0.2040268148129029,"score_spread":0.1884602543525964,"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."}}