{"id":"W2071586469","doi":"10.1016/j.jcis.2014.10.049","title":"Poly (lactic-co-glycolic acid) particles prepared by microfluidics and conventional methods. Modulated particle size and rheology","year":2014,"lang":"en","type":"article","venue":"Journal of Colloid and Interface Science","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"PLGA; Particle size; Rheology; Microfluidics; Particle-size distribution; Materials science; Chemical engineering; Particle (ecology); Glycolic acid; Settling; Aqueous solution; Nanotechnology; Chemistry; Lactic acid; Nanoparticle; Composite material; Organic chemistry; Thermodynamics","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":[0.001407388,0.0001107077,0.0001987184,0.00008637796,0.0001141857,0.00008747092,0.0001246142,0.00005337989,0.00001484147],"category_scores_gemma":[0.0002893949,0.0000961086,0.00001704623,0.0003412181,0.0006384641,0.0004306231,0.00005333406,0.0001467124,7.398722e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004364072,"about_ca_system_score_gemma":0.00004161086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002244595,"about_ca_topic_score_gemma":9.646605e-8,"domain_scores_codex":[0.9990741,0.00004825524,0.0003823582,0.0001444805,0.0001477786,0.0002030152],"domain_scores_gemma":[0.9993782,0.00009522778,0.0001346838,0.00008428947,0.0002188916,0.00008867574],"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":[0.00003267188,0.00001396595,0.000529469,0.00001453924,0.00001631047,2.023725e-7,0.0002668662,7.169979e-7,0.9837184,0.001639837,0.001179381,0.01258767],"study_design_scores_gemma":[0.0004565086,0.0002291257,0.002127596,0.00002993751,0.00001329334,0.000150855,0.000134319,0.007801272,0.9843224,0.0007020378,0.003927554,0.0001051046],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7701908,0.006865991,0.2224536,0.0001735727,0.0001128906,0.00005646857,0.000003196904,0.00002545796,0.0001181165],"genre_scores_gemma":[0.9913558,0.0002060391,0.008196018,0.0001105348,0.00002041983,0.000002055576,3.330144e-7,0.000008319859,0.0001004268],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2211651,"threshold_uncertainty_score":0.3919195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007960927451001961,"score_gpt":0.2891877484482707,"score_spread":0.2812268209972688,"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."}}