{"id":"W1486450196","doi":"10.18637/jss.v069.i04","title":"Parallel and Other Simulations in<i>R</i>Made Easy: An End-to-End Study","year":2016,"lang":"en","type":"article","venue":"Journal of Statistical Software","topic":"Data Analysis with R","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Eidgenössische Technische Hochschule Zürich","keywords":"Computer science; Graphics; Computation; Set (abstract data type); Table (database); Scale (ratio); Contrast (vision); Contingency table; Algorithm; Computational science; Data mining; Computer graphics (images); Artificial intelligence; Programming language; Machine learning","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":[0.01936333,0.002010673,0.00180999,0.001100664,0.001185595,0.004237211,0.003922253,0.002088184,0.04112123],"category_scores_gemma":[0.1033371,0.001406739,0.003138833,0.001938623,0.001454644,0.005026298,0.004670346,0.00511322,0.02257074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001198721,"about_ca_system_score_gemma":0.002245857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002667231,"about_ca_topic_score_gemma":0.003048741,"domain_scores_codex":[0.9847489,0.01021779,0.0008219755,0.001518807,0.002293111,0.0003994353],"domain_scores_gemma":[0.9234363,0.05172091,0.001780143,0.01603673,0.006014254,0.0010117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001381766,0.0006133857,0.00599524,0.002195496,0.0007405416,0.00102295,0.001420893,0.1826917,0.006981722,0.249892,0.2587219,0.2883425],"study_design_scores_gemma":[0.0005006089,0.0004905591,0.001932579,0.0006955309,0.0001948745,0.000514462,0.0002993953,0.4262099,0.01277388,0.2492163,0.3069381,0.0002338124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004686392,0.0005697152,0.9582276,0.002665828,0.0006685382,0.0004530544,0.002877964,0.01622268,0.01362823],"genre_scores_gemma":[0.03760629,0.001007114,0.9289778,0.001995945,0.0003229606,0.002083768,0.005223176,0.01602118,0.006761802],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04112123,"threshold_uncertainty_score":0.1375642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02613877045930482,"score_gpt":0.3101626526354363,"score_spread":0.2840238821761315,"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."}}