{"id":"W1515933475","doi":"10.48550/arxiv.hep-ph/0006166","title":"Monte Carlo Generators and the CCFM Equation","year":2000,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Particle Physics","funders":"","keywords":"Monte Carlo method; Statistical physics; Physics; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001204757,0.0001904285,0.0001841073,0.00004847061,0.00007626224,0.00007648412,0.0001363969,0.0001673481,0.00006360083],"category_scores_gemma":[0.00001475446,0.0001442489,0.00004866876,0.00004366689,0.0000370145,0.00006035734,0.00007599482,0.0002973701,0.0000183765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003177156,"about_ca_system_score_gemma":0.00001478963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001115336,"about_ca_topic_score_gemma":0.00001803967,"domain_scores_codex":[0.9993286,0.00002473411,0.0001917703,0.0002088355,0.0001050646,0.000141071],"domain_scores_gemma":[0.9995922,0.00002882242,0.00004529848,0.0002719212,0.00002357442,0.00003813911],"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":[0.0000085798,0.000003106633,0.003488825,0.0001218902,0.00003685403,9.459624e-7,0.000489292,0.9926634,0.000006179391,0.0000296133,0.0001732705,0.002978007],"study_design_scores_gemma":[0.0008804464,0.000009017309,0.02921574,0.0001116105,0.000107504,0.000002168842,0.00003152632,0.9620621,0.002579955,0.0004799067,0.004026345,0.0004937288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908739,0.002169332,0.004393783,0.0001408974,0.0004421771,0.0002436851,0.000007064726,0.000221294,0.001507819],"genre_scores_gemma":[0.9969884,0.002015114,0.0003097758,0.00007532235,0.0002395817,0.00006275735,0.00001786492,0.00003797258,0.0002532323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03060138,"threshold_uncertainty_score":0.5882298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02230381336558973,"score_gpt":0.2026686144903519,"score_spread":0.1803648011247621,"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."}}