{"id":"W3008804997","doi":"10.1109/wsc40007.2019.9004689","title":"Investigation of Versatile Datatypes for Representing Time in Discrete Event Simulation","year":2019,"lang":"en","type":"article","venue":"","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Timeline; Computer science; Event (particle physics); Discrete event simulation; Range (aeronautics); Point (geometry); Algorithm; Theoretical computer science; Simulation; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01681276,0.001603782,0.001128461,0.001730922,0.001105319,0.005318385,0.006124943,0.002123102,0.004466162],"category_scores_gemma":[0.05509298,0.001014756,0.002781284,0.002925677,0.002005816,0.009539501,0.004261566,0.004519243,0.001092387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00287163,"about_ca_system_score_gemma":0.003767251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006704663,"about_ca_topic_score_gemma":0.005409052,"domain_scores_codex":[0.9855327,0.005317997,0.0033157,0.001281595,0.003876373,0.0006756991],"domain_scores_gemma":[0.9332713,0.03594833,0.00427105,0.0177983,0.007638947,0.001072104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002286582,0.0006884295,0.01662458,0.002097213,0.0003435115,0.0006480062,0.002487051,0.3264033,0.01035185,0.4584432,0.01277788,0.1668485],"study_design_scores_gemma":[0.000332996,0.0004188854,0.001002182,0.000776761,0.0001607853,0.0005067265,0.0006723206,0.7504337,0.02814233,0.1166905,0.1006437,0.0002191987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03459132,0.0007463665,0.9500518,0.0007638311,0.0003363683,0.0005336521,0.003013756,0.006231542,0.003731327],"genre_scores_gemma":[0.2555208,0.0008268288,0.7339084,0.000536769,0.00008334468,0.001074081,0.004486247,0.001552766,0.00201069],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01681276,"threshold_uncertainty_score":0.08891541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1335250988629363,"score_gpt":0.4466005363720053,"score_spread":0.313075437509069,"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."}}