{"id":"W2045735525","doi":"10.1063/1.1586693","title":"Constant-number Monte Carlo simulation of aggregating and fragmenting particles","year":2003,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Coagulation and Flocculation Studies","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Devon Energy (Canada); Natural Resources Canada","funders":"","keywords":"Monte Carlo method; Constant (computer programming); Kernel (algebra); Statistical physics; Particle number; Population; Mathematics; Materials science; Physics; Volume (thermodynamics); Thermodynamics; Computer science; Combinatorics; Statistics","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":[0.001026174,0.0003103619,0.0007121714,0.0006517768,0.0009058214,0.000671546,0.001587065,0.001117007,0.001166522],"category_scores_gemma":[0.002652843,0.0003049847,0.0005177028,0.0008282958,0.0009620517,0.0006992692,0.0005113319,0.0007555063,0.000165152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00138163,"about_ca_system_score_gemma":0.001403534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01878531,"about_ca_topic_score_gemma":0.008287294,"domain_scores_codex":[0.99965,0.00009323814,0.00001673079,0.00005959841,0.0001149606,0.00006545542],"domain_scores_gemma":[0.9985576,0.000864123,0.00009624138,0.0001864654,0.0002063815,0.0000891529],"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":[0.00005067047,0.00005720341,0.0009605182,0.00002052799,0.00001553545,0.00007588454,0.00006516308,0.9728282,0.002109971,0.02088965,0.0002613403,0.002665314],"study_design_scores_gemma":[0.00000530896,0.000004701796,0.00007582346,7.047118e-7,0.000001368622,0.000004671747,0.000002406158,0.9985999,0.0004268157,0.0007444039,0.000130847,0.000002959826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6602532,0.0002969397,0.3228709,0.0002432734,0.00009824063,0.0001844383,0.0002378951,0.000446089,0.01536914],"genre_scores_gemma":[0.9133725,0.0001903337,0.08267502,0.0000697556,0.00001511271,0.0002574695,0.0002727216,0.00008664707,0.003060392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01878531,"threshold_uncertainty_score":0.03735197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02044009704753924,"score_gpt":0.261680320856885,"score_spread":0.2412402238093458,"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."}}