{"id":"W4225291709","doi":"10.1145/3529538.3529992","title":"SYCLops: A SYCL Specific LLVM to MLIR Converter","year":2022,"lang":"en","type":"article","venue":"International Workshop on OpenCL","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Exploit; Computer science; Computer security","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":[0.001077135,0.00125285,0.0006250514,0.0009532033,0.0004654577,0.002965592,0.00206418,0.0008550573,0.02462512],"category_scores_gemma":[0.004325483,0.0007581659,0.0007077378,0.000529848,0.0006763889,0.003136352,0.003266378,0.002554939,0.01235372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041192,"about_ca_system_score_gemma":0.001452452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001501502,"about_ca_topic_score_gemma":0.001948722,"domain_scores_codex":[0.9986783,0.0001538644,0.0001309891,0.0002588085,0.000530298,0.0002478782],"domain_scores_gemma":[0.9983209,0.0003114047,0.00008677151,0.0006180551,0.000556117,0.0001067745],"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":[0.002566194,0.0005939711,0.003763279,0.001078647,0.0001663945,0.001053192,0.0009391231,0.01236577,0.1107193,0.07717124,0.4136359,0.3759468],"study_design_scores_gemma":[0.0005132335,0.0004774421,0.002372867,0.0003027222,0.0001118235,0.000741065,0.000373455,0.1662222,0.2736473,0.05048757,0.5045308,0.0002194922],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0244856,0.0006047823,0.4845253,0.0005028755,0.0007353486,0.0005747799,0.003329651,0.4324871,0.05275458],"genre_scores_gemma":[0.4593329,0.0006455457,0.2995132,0.003338936,0.000446942,0.001181097,0.0201462,0.1274856,0.08790963],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02462512,"threshold_uncertainty_score":0.08237922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02926183344336735,"score_gpt":0.2936517919966401,"score_spread":0.2643899585532727,"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."}}