{"id":"W4402364932","doi":"10.1063/5.0223361","title":"On the use of reactive multiparticle collision dynamics to gather particulate level information from simulations of epidemic models","year":2024,"lang":"en","type":"article","venue":"AIP Advances","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Collision; Particulates; Dynamics (music); Statistical physics; Computer science; Physics; Chemistry; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003465589,0.0001134087,0.00026636,0.00004589152,0.00006727644,0.0000150124,0.0001034344,0.00004560388,0.00001685084],"category_scores_gemma":[0.008032545,0.00006671911,0.00007552171,0.0002580514,0.00007978885,0.0006237019,0.00007883429,0.00009353346,0.00001696367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009746443,"about_ca_system_score_gemma":0.00001583624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002777831,"about_ca_topic_score_gemma":0.0002490726,"domain_scores_codex":[0.9988853,0.0001222808,0.0005156061,0.0001453881,0.0001900344,0.0001413919],"domain_scores_gemma":[0.9808615,0.01856555,0.0001719176,0.0002490287,0.0001183483,0.00003364492],"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":[0.00008668624,0.00007151964,0.001838348,0.00005506524,0.00007563598,4.406072e-7,0.002306186,0.8467922,0.0006129307,0.1426696,0.00055307,0.004938308],"study_design_scores_gemma":[0.00007008103,0.00005033626,0.001171059,0.0001334074,0.00002783662,5.557723e-8,0.0001559491,0.6469738,0.001174875,0.3492686,0.0009138541,0.0000601076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.772491,0.00009891242,0.2249659,0.001641706,0.00005726244,0.0003562344,0.000304953,0.00004193589,0.00004212988],"genre_scores_gemma":[0.9869078,0.00004944217,0.01255753,0.0004113914,0.0000107284,0.00003022937,0.000008425572,0.000008026212,0.00001647105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2144168,"threshold_uncertainty_score":0.9616287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4202853571473154,"score_gpt":0.43661969727667,"score_spread":0.01633434012935464,"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."}}