{"id":"W3103321439","doi":"10.3390/pharmaceutics12111095","title":"Manufacturing Considerations for the Development of Lipid Nanoparticles Using Microfluidics","year":2020,"lang":"en","type":"article","venue":"Pharmaceutics","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":302,"is_retracted":false,"has_abstract":true,"ca_institutions":"Precision Nanosystems (Canada)","funders":"Engineering and Physical Sciences Research Council; Cancer Research UK","keywords":"Dispersity; Microfluidics; Chemistry; Nanoparticle; Nanotechnology; Buffer (optical fiber); Payload (computing); Nucleic acid; Particle size; Chromatography; Materials science; Computer science; Biochemistry; Organic chemistry","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":[0.002827084,0.0009634073,0.0005341308,0.0007695774,0.000629545,0.001163993,0.0007260844,0.0009102772,0.002221925],"category_scores_gemma":[0.002929607,0.0005769526,0.0007684437,0.0002527218,0.0004368026,0.0007582454,0.0005271379,0.0007229828,0.001542378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008131156,"about_ca_system_score_gemma":0.001041566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007585848,"about_ca_topic_score_gemma":0.001581953,"domain_scores_codex":[0.9987342,0.0002165934,0.0001934505,0.0001969632,0.0005721673,0.00008659204],"domain_scores_gemma":[0.9987121,0.0005541588,0.0002801913,0.00009497177,0.0002997649,0.00005883579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001442085,0.0001033587,0.0007687076,0.001012523,0.00004070152,0.0004249658,0.0001050095,0.00263008,0.9576502,0.004348872,0.0009863634,0.03178488],"study_design_scores_gemma":[0.0001078996,0.001278533,0.002180433,0.0002464693,0.0001576189,0.001158005,0.0001355245,0.01581813,0.8931911,0.002385856,0.08324984,0.00009064039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.224359,0.03636336,0.6951157,0.009046688,0.002986341,0.004018296,0.001153995,0.002207553,0.02474918],"genre_scores_gemma":[0.2528026,0.0125209,0.7259138,0.0009968819,0.0005494405,0.001646919,0.0006508993,0.0001495504,0.004769003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002827084,"threshold_uncertainty_score":0.01495117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1552105268611953,"score_gpt":0.3512033802500744,"score_spread":0.1959928533888791,"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."}}