{"id":"W2105775946","doi":"10.1002/ceat.201000251","title":"Simulation of Polymerization Kinetics and Molecular Weight Development in the Microwave‐Activated Emulsion Polymerization of Styrene using EMULPOLY<sup>®</sup>","year":2010,"lang":"en","type":"article","venue":"Chemical Engineering & Technology","topic":"Microwave-Assisted Synthesis and Applications","field":"Chemistry","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; Consejo Nacional de Ciencia y Tecnología","keywords":"Emulsion polymerization; Styrene; Microwave; Kinetics; Polymerization; Monomer; Emulsion; Polymer chemistry; Materials science; Reaction rate constant; Chemistry; Chemical engineering; Copolymer; Polymer; Organic chemistry; Physics","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":[0.00004672991,0.0001535507,0.0002089354,0.0001852657,0.00002439605,0.000007106823,0.0001939897,0.000337166,0.00001808845],"category_scores_gemma":[0.0001621135,0.0001428397,0.00002912423,0.000475387,0.00009151165,0.00003266568,0.00006412798,0.0002461825,2.701671e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002760179,"about_ca_system_score_gemma":0.00001655218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005698424,"about_ca_topic_score_gemma":4.207751e-7,"domain_scores_codex":[0.9990868,0.00000569642,0.0004118819,0.0002128863,0.0001162407,0.0001664781],"domain_scores_gemma":[0.9993879,0.00009039897,0.0001520012,0.0002904974,0.0000529944,0.00002621616],"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":[0.00000648704,0.00008829669,0.000225024,0.00007853287,0.00001461228,4.268289e-7,0.0001339178,0.01205795,0.9815355,0.0004330763,2.393376e-7,0.005425948],"study_design_scores_gemma":[0.0002008013,0.000004619595,0.00005189525,0.00006334182,0.00001708096,0.000005637823,0.000039282,0.1148858,0.8844666,0.00003360069,0.0001152622,0.0001161208],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9601737,0.0001322821,0.03941609,0.00008064099,0.000009825124,0.00008789232,0.000005366099,0.00005439821,0.00003977432],"genre_scores_gemma":[0.9908189,0.000006154407,0.009066628,0.000006434732,0.00001431361,0.00001507074,0.00004555888,0.00002480507,0.000002149754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1028278,"threshold_uncertainty_score":0.5824834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0058464698879047,"score_gpt":0.2084067986979128,"score_spread":0.2025603288100081,"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."}}