{"id":"W2162484733","doi":"10.1002/cjce.20091","title":"Dynamic evolution of the particle size distribution in suspension polymerization reactors: A comparative study on Monte Carlo and sectional grid methods","year":2008,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Coagulation and Flocculation Studies","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Breakage; Monte Carlo method; Coalescence (physics); Materials science; Suspension polymerization; Polymerization; Suspension (topology); Particle (ecology); Particle size; Mechanics; Thermodynamics; Chemical engineering; Chemistry; Composite material; Polymer; Physics; Mathematics; Physical chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001731226,0.0002955032,0.0005507536,0.000708395,0.0003463754,0.0005447478,0.0008002243,0.0007038185,0.0008014677],"category_scores_gemma":[0.003835734,0.000391554,0.0004449443,0.0005807879,0.0004680282,0.0006088751,0.0003465254,0.0004075679,0.000164943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008053703,"about_ca_system_score_gemma":0.0007333862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006796939,"about_ca_topic_score_gemma":0.003715344,"domain_scores_codex":[0.9996426,0.0001828834,0.00001567835,0.00003160519,0.0001041375,0.0000229896],"domain_scores_gemma":[0.9969408,0.002316508,0.0001582501,0.0002102921,0.0003142284,0.00005986617],"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":[0.00007787068,0.00005616335,0.003303371,0.00004490502,0.00002976031,0.00004317769,0.00005088886,0.9669452,0.002958101,0.006029665,0.000123911,0.02033699],"study_design_scores_gemma":[0.000002867642,0.000007379483,0.0001252328,0.00000142844,0.000001459858,0.000005575912,0.000001842263,0.9990867,0.0005029303,0.0001951719,0.0000674956,0.000001943335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2237187,0.0005190183,0.7709762,0.0001195518,0.0000364019,0.00007716675,0.00006504012,0.0007632409,0.003724696],"genre_scores_gemma":[0.85345,0.0002780451,0.1450291,0.00003956756,0.00001558398,0.0001125873,0.00008401142,0.0001608626,0.0008301567],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006796939,"threshold_uncertainty_score":0.01351476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0192441264891678,"score_gpt":0.2547462246898812,"score_spread":0.2355020982007134,"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."}}