{"id":"W2751901133","doi":"10.1145/3124452","title":"MiCOMP","year":2017,"lang":"en","type":"article","venue":"ACM Transactions on Architecture and Code Optimization","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Horizon 2020 Framework Programme; City University of New York","keywords":"Computer science; Compiler; Optimizing compiler; Parallel computing; Heuristics; Speedup; Program optimization; Code (set theory); Sequence (biology); Set (abstract data type); Algorithm; Programming language","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":[],"consensus_categories":[],"category_scores_codex":[0.0001052626,0.0001393271,0.0001202121,0.0001361122,0.001036442,0.0004210682,0.000958884,0.0000729724,0.00001529971],"category_scores_gemma":[0.00003832119,0.000127905,0.00004781597,0.00008618621,0.00006707256,0.0002974086,0.00003812999,0.0001748578,0.000005445321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001270975,"about_ca_system_score_gemma":0.00002144735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001000705,"about_ca_topic_score_gemma":0.00001226798,"domain_scores_codex":[0.9991825,0.00004191726,0.0001432091,0.0003358783,0.0001361436,0.0001603539],"domain_scores_gemma":[0.9985555,0.00005589973,0.0001057518,0.001155002,0.00005253508,0.00007535522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009257702,0.00003715565,0.00001814754,0.00000447501,0.00001118632,0.000001650236,0.000185294,0.796595,0.00002770055,0.001086115,0.00005728866,0.2019667],"study_design_scores_gemma":[0.0004525917,0.0001318511,0.0003922858,0.00003798254,0.00001273869,0.00003311413,0.000005634382,0.9859782,0.001971734,0.008091355,0.002618164,0.0002742754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002776965,0.00003243623,0.9926454,0.004301288,0.0001364148,0.000126495,0.000005314745,0.0003833098,0.002091596],"genre_scores_gemma":[0.2998635,0.0001329688,0.6992134,0.0004175422,0.00002243301,0.00001412528,0.000003145465,0.00001025603,0.0003226327],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2995858,"threshold_uncertainty_score":0.7971582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01697613334756822,"score_gpt":0.2636359512709955,"score_spread":0.2466598179234273,"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."}}