{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008547604,0.001651427,0.001007934,0.001560388,0.001320136,0.003604826,0.003766927,0.001403601,0.1161418],"category_scores_gemma":[0.003430771,0.0009457798,0.001483169,0.001863656,0.0006383099,0.0038656,0.004271458,0.002105442,0.09595275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001282962,"about_ca_system_score_gemma":0.00187246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00309099,"about_ca_topic_score_gemma":0.003879295,"domain_scores_codex":[0.9982955,0.0001774075,0.000115217,0.0003873922,0.0007562746,0.0002682877],"domain_scores_gemma":[0.9983932,0.0001995591,0.00008198651,0.0006543149,0.000528166,0.0001427038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006917719,0.0002067341,0.002045602,0.0008828365,0.0001001088,0.0003379043,0.0002275368,0.008043678,0.009214886,0.05664051,0.563743,0.3578655],"study_design_scores_gemma":[0.00009473467,0.0001039411,0.001140919,0.00009743883,0.00003512709,0.0003648738,0.00008230659,0.03135593,0.01140065,0.01973437,0.9355245,0.00006528023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.0140793,0.002389315,0.2509251,0.002219183,0.002034644,0.0007322422,0.02301103,0.2738186,0.4307906],"genre_scores_gemma":[0.1663449,0.002517744,0.3482848,0.003573933,0.0008455182,0.00129147,0.1313029,0.05425435,0.2915845],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1161418,"threshold_uncertainty_score":0,"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."}}