{"id":"W3048458458","doi":"10.1145/3386569.3392486","title":"NASOQ","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Computer science; Solver; Scalability; Benchmark (surveying); Quadratic programming; General-purpose computing on graphics processing units; Algorithm; Set (abstract data type); Graphics; Mathematical optimization; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001687358,0.001576857,0.001237063,0.0007745351,0.001112929,0.002232719,0.003401247,0.00148728,0.04690335],"category_scores_gemma":[0.006576101,0.0006278573,0.001338043,0.0009078844,0.001011119,0.002081285,0.002822042,0.002568996,0.01282478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001330625,"about_ca_system_score_gemma":0.003975506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00787803,"about_ca_topic_score_gemma":0.01518432,"domain_scores_codex":[0.9983442,0.0003097414,0.0001090373,0.0002490205,0.000756354,0.0002317377],"domain_scores_gemma":[0.9977369,0.0008396491,0.0001344882,0.0003187971,0.000836763,0.000133402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005280273,0.0003356654,0.002152174,0.00126623,0.0001285547,0.0002638982,0.0001738936,0.319318,0.004379795,0.1477479,0.2372259,0.2864799],"study_design_scores_gemma":[0.0002185836,0.0001384898,0.0003148772,0.0001009075,0.00002490747,0.0001016981,0.0000852969,0.814788,0.003357675,0.05634714,0.1244846,0.00003778744],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01796744,0.002323343,0.806381,0.001875356,0.001559265,0.0007923894,0.006201717,0.02897963,0.1339198],"genre_scores_gemma":[0.1711773,0.001876096,0.736414,0.001891783,0.0003915496,0.001398584,0.01663392,0.009947055,0.0602697],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04690335,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.034560357211684,"score_gpt":0.2599070710811662,"score_spread":0.2253467138694822,"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."}}