{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002092595,0.0003017198,0.0001799513,0.0001370758,0.00007783176,0.00031857,0.000295495,0.0005832076,0.0006380837],"category_scores_gemma":[0.000360958,0.0001167265,0.0003457588,0.00009500372,0.0002142347,0.0002120375,0.0001385695,0.0002293313,0.0002720955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003291019,"about_ca_system_score_gemma":0.0001887078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001100661,"about_ca_topic_score_gemma":0.0005245184,"domain_scores_codex":[0.9999123,0.00002233098,0.000004723986,0.00002620109,0.00002375878,0.00001067426],"domain_scores_gemma":[0.9999061,0.0000580186,0.00001513305,0.000007614623,0.0000105769,0.00000257834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001326191,0.00006067523,0.0008200568,0.0001345737,0.0000152918,0.0001469932,0.0000696241,0.6376911,0.3504785,0.003586143,0.0001643867,0.006700038],"study_design_scores_gemma":[0.000006279097,0.00003494698,0.0001729814,0.000001614043,0.000003338937,0.00001058552,0.000004372902,0.9778757,0.02140457,0.0001425389,0.0003397827,0.00000327684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4328307,0.000534459,0.5562095,0.0002158769,0.0000513831,0.0002194593,0.0003650785,0.0005304693,0.00904297],"genre_scores_gemma":[0.9760699,0.0003023609,0.01986797,0.00003784952,0.000007465327,0.0001771605,0.0001026377,0.0000279352,0.003406715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001100661,"threshold_uncertainty_score":0.002387822,"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."}}