{"id":"W2294671177","doi":"10.5555/2872965.2872986","title":"Improving the flexibility of simulation modeling with aspects","year":2015,"lang":"en","type":"article","venue":"","topic":"Modeling, Simulation, and Optimization","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Debugging; Executable; Tracing; Flexibility (engineering); TRACE (psycholinguistics); Robustness (evolution); Metadata; Software engineering; Visualization; Data mining; Distributed computing; Programming language; World Wide Web","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":[0.0006037875,0.00008181013,0.0001166412,0.00003175739,0.00006188671,0.00001962049,0.00007789049,0.00004326077,0.00001974837],"category_scores_gemma":[0.0003891838,0.00004753981,0.00002597838,0.0001195291,0.00002060522,0.0001745269,0.0000209959,0.00005341226,0.000001552621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003583521,"about_ca_system_score_gemma":0.0000796901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001202319,"about_ca_topic_score_gemma":0.0000920644,"domain_scores_codex":[0.9991922,0.00004175589,0.0002668821,0.0001387664,0.0002640392,0.00009637701],"domain_scores_gemma":[0.9988928,0.0001712261,0.0001287606,0.0003064213,0.0004623552,0.00003846747],"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":[0.00003427687,0.00002797972,0.0001380681,0.00002244554,0.000006390749,6.307173e-8,0.001026946,0.9727061,0.0000142966,0.02573086,0.00000654234,0.0002859634],"study_design_scores_gemma":[0.0003364688,0.00003572692,0.000005164391,0.00001006731,0.00002389142,3.666795e-7,0.0002960427,0.925083,0.0001785027,0.07396502,0.000002875825,0.00006281795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2869799,0.000009934143,0.7096398,0.00002353709,0.000022215,0.0001859007,4.684497e-7,0.00005205481,0.003086144],"genre_scores_gemma":[0.934868,4.716942e-7,0.06494433,0.00001881413,0.00004352371,0.000002722846,0.000003380751,0.0000129568,0.0001057451],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6478881,"threshold_uncertainty_score":0.1938617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.156482839079385,"score_gpt":0.3399071735327939,"score_spread":0.1834243344534089,"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."}}