{"id":"W4399851393","doi":"10.1145/3656389","title":"Optimistic Stack Allocation and Dynamic Heapification for Managed Runtimes","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada)","funders":"IBM Canada","keywords":"Stack (abstract data type); Computer science; Parallel computing; Distributed computing; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000410134,0.0001038663,0.0001008789,0.0001087199,0.0001182151,0.0003210998,0.0009611074,0.00004680422,4.789243e-7],"category_scores_gemma":[0.0004987488,0.00007629324,0.00004880968,0.00029523,0.00004587323,0.0001997388,0.0002835963,0.00008888812,0.000001033841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002622648,"about_ca_system_score_gemma":0.00001405944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004279879,"about_ca_topic_score_gemma":3.885259e-7,"domain_scores_codex":[0.9992582,0.00000675767,0.0001630345,0.0002929633,0.0001363276,0.0001426845],"domain_scores_gemma":[0.9993554,0.0001209699,0.00009555567,0.0002870989,0.0001160691,0.0000248755],"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":[0.00002624097,0.0001181455,0.0002842089,0.001254069,0.00008763375,7.546631e-7,0.003591908,0.0005793223,0.009362428,0.2349312,0.003907945,0.7458561],"study_design_scores_gemma":[0.0004823823,0.0006919198,0.002107913,0.001283367,0.0001043818,0.00002902989,0.0008188781,0.8848321,0.05455068,0.04762246,0.006848867,0.0006279791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09151363,0.003516517,0.8833693,0.01540906,0.0003405132,0.002137676,0.000006742285,0.002637329,0.001069212],"genre_scores_gemma":[0.6528468,0.00003658081,0.3466529,0.00004485418,0.00001603397,0.00005880383,0.00000215684,0.000009944752,0.0003318695],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8842528,"threshold_uncertainty_score":0.3111148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01276157674847713,"score_gpt":0.2883359293097509,"score_spread":0.2755743525612738,"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."}}