{"id":"W2809203089","doi":"10.1002/mren.201800020","title":"A Simple Monte Carlo Method for Modeling Arborescent Polymer Production in Continuous Stirred Tank Reactor","year":2018,"lang":"en","type":"article","venue":"Macromolecular Reaction Engineering","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Continuous stirred-tank reactor; Monte Carlo method; Monomer; Copolymer; Chemistry; Materials science; Batch reactor; Inflow; Polymer chemistry; Polymer; Thermodynamics; Mechanics; Physical chemistry; Physics; Organic chemistry; Mathematics; Catalysis","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":[0.0007790115,0.0005687266,0.0007051422,0.0004244065,0.0006003921,0.000690895,0.001141309,0.00125996,0.001875188],"category_scores_gemma":[0.001343978,0.0006808015,0.0007222804,0.0003919151,0.0006868172,0.0005369845,0.0003202702,0.0007136308,0.0002366987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001450191,"about_ca_system_score_gemma":0.001914928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02542939,"about_ca_topic_score_gemma":0.01112226,"domain_scores_codex":[0.9998129,0.00005626871,0.000008400992,0.00003269996,0.00005744103,0.0000323469],"domain_scores_gemma":[0.99925,0.0005076294,0.00007150966,0.00002723987,0.0001031754,0.00004045922],"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":[0.000006922925,0.000007252215,0.0001093428,0.000005104357,0.000004047351,0.00001083001,0.00000349369,0.9975942,0.0003958637,0.001290982,0.00002635716,0.0005456242],"study_design_scores_gemma":[0.000002773875,0.000002673995,0.00001635599,5.737895e-7,9.494797e-7,0.00000113016,5.114513e-7,0.9996662,0.0001012052,0.0001506665,0.00005558787,0.000001280465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0993382,0.0002470646,0.8931713,0.0002004174,0.00004901292,0.0001272078,0.0002019445,0.0004077228,0.006257081],"genre_scores_gemma":[0.8693693,0.0002639919,0.1226183,0.00008432598,0.00002952801,0.0005492311,0.0002065954,0.0001032266,0.006775344],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02542939,"threshold_uncertainty_score":0.05056274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009592349115965215,"score_gpt":0.2472333981391777,"score_spread":0.2376410490232125,"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."}}