{"id":"W4247144579","doi":"10.1145/3140659.3080216","title":"LogCA","year":2017,"lang":"en","type":"article","venue":"ACM SIGARCH Computer Architecture News","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"Scheme for Promotion of Academic and Research Collaboration; University of Wisconsin-Madison; National Science Foundation","keywords":"Computer science; Oracle; Interface (matter); Variety (cybernetics); Computer architecture; Embedded system; Efficient energy use; Parallel computing; Computer engineering; Software engineering; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0003390647,0.0002987247,0.0003087237,0.0002042521,0.00096997,0.001114322,0.008089072,0.0001139686,0.00001187505],"category_scores_gemma":[0.0002666976,0.0002602218,0.0001666522,0.0001392421,0.000159912,0.0004050932,0.003977723,0.0004487235,0.00007871585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003093205,"about_ca_system_score_gemma":0.0000881248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000818909,"about_ca_topic_score_gemma":0.00002369849,"domain_scores_codex":[0.9978157,0.0001442478,0.0003120855,0.0007665533,0.0004086965,0.0005527716],"domain_scores_gemma":[0.9945664,0.0002679936,0.0002460302,0.004586785,0.0001162337,0.0002165776],"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":[0.000009003062,0.00007274278,0.001969112,0.00001766512,0.00004012867,0.00006846362,0.0008624617,0.007987651,0.0001730524,0.01141506,0.02346059,0.9539241],"study_design_scores_gemma":[0.001933763,0.0008157025,0.03357715,0.0002041372,0.00002018598,0.0003610749,0.00000460428,0.4880485,0.005119991,0.2324332,0.2357455,0.001736275],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002198751,0.00005846965,0.9793801,0.0104467,0.0006970532,0.0002404354,0.000001453155,0.001056309,0.005920717],"genre_scores_gemma":[0.2054376,0.00002272058,0.7918811,0.001822873,0.0005556905,0.00001551811,0.000003533658,0.00002046353,0.0002404942],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9521878,"threshold_uncertainty_score":0.999985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02216156391471025,"score_gpt":0.2852843903068958,"score_spread":0.2631228263921855,"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."}}