{"id":"W2547589727","doi":"10.1109/ccece.2016.7726757","title":"Object layout optimization in the JVM based on affinity","year":2016,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada); University of New Brunswick","funders":"Atlantic Canada Opportunities Agency; New Brunswick Innovation Foundation","keywords":"Computer science; Java; Cache; Operating system; Locality; Object (grammar); Parallel computing; IBM; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003477006,0.0004701803,0.0007039366,0.0005446217,0.0006101854,0.0008716006,0.001150097,0.000450888,0.002103533],"category_scores_gemma":[0.00130186,0.0003611119,0.0005502583,0.001180666,0.0004014852,0.0009581708,0.000822917,0.0005570422,0.0006014835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008400481,"about_ca_system_score_gemma":0.0009704142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003270574,"about_ca_topic_score_gemma":0.004706915,"domain_scores_codex":[0.9994693,0.00008965696,0.00002981131,0.00008295077,0.0002284925,0.0000997596],"domain_scores_gemma":[0.999338,0.0001678657,0.0000752463,0.0002358568,0.0001415928,0.00004136303],"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":[0.0005221241,0.0003894384,0.007766532,0.0003768675,0.0001075178,0.0003125724,0.0003998503,0.2613406,0.2353187,0.02003856,0.009492027,0.4639351],"study_design_scores_gemma":[0.0001211366,0.0003258915,0.003588624,0.00002084279,0.00007360742,0.0002790985,0.0001037748,0.8863776,0.07922093,0.01238575,0.0174432,0.00005954183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2313271,0.00119693,0.745387,0.0002808954,0.0001605929,0.0001004555,0.0001067817,0.01127856,0.01016166],"genre_scores_gemma":[0.5985739,0.000261998,0.393876,0.000138237,0.00004375912,0.0001034876,0.0002957089,0.001343061,0.005363949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003270574,"threshold_uncertainty_score":0.007037044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01895252008704763,"score_gpt":0.2537519398584979,"score_spread":0.2347994197714502,"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."}}