{"id":"W3208591130","doi":"10.1145/3476485","title":"Implementation of the article &amp;quot;Hybrid, scalable, trace-driven performance modeling of GPGPUs&amp;quot;","year":2021,"lang":"en","type":"dataset","venue":"Artifact Digital Object Group","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"TRACE (psycholinguistics); Scalability; Computer science; Operating system; Philosophy","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":[0.00084702,0.00128391,0.0007567411,0.001525957,0.0008418346,0.001434156,0.002683735,0.00102758,0.02726583],"category_scores_gemma":[0.003563989,0.0004495571,0.00108041,0.002220384,0.0003458524,0.0008904617,0.0009262979,0.00131879,0.02762889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001291062,"about_ca_system_score_gemma":0.002483686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03291494,"about_ca_topic_score_gemma":0.08954615,"domain_scores_codex":[0.999273,0.00008822,0.00007728184,0.0001968223,0.0002563342,0.0001082662],"domain_scores_gemma":[0.9981228,0.0002914593,0.00008492505,0.0006995761,0.0006610085,0.0001403375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003394357,0.0002188051,0.001859917,0.000617608,0.00006676756,0.00003873434,0.00003356612,0.008671982,0.001363906,0.001739403,0.9639706,0.02107931],"study_design_scores_gemma":[0.001396032,0.0003406159,0.01606596,0.0002259752,0.00009883881,0.0002390352,0.0001909838,0.09741066,0.01295903,0.008629375,0.8623277,0.0001158173],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004752556,0.0001166042,0.003726237,0.0003493609,0.000218767,0.0001647758,0.9758661,0.00897652,0.005828924],"genre_scores_gemma":[0.008367596,0.00008343335,0.007731701,0.0001161982,0.00002350535,0.0002460296,0.979916,0.0004454984,0.003069973],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03291494,"threshold_uncertainty_score":0.09121323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02290514651777953,"score_gpt":0.262152581652043,"score_spread":0.2392474351342635,"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."}}