{"id":"W2059346393","doi":"10.5555/1251028.1251050","title":"VXA: a virtual architecture for durable compressed archives","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; x86; Virtualization; Operating system; Executable; Architecture; Embedded system; Host (biology); Computer architecture; Cloud computing; Software","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":[0.001324428,0.000557652,0.0003881088,0.0009749946,0.001005911,0.003245555,0.004240282,0.0009438004,0.011704],"category_scores_gemma":[0.004334417,0.0006381657,0.0005336885,0.0006901862,0.001140365,0.003502478,0.003483247,0.001473445,0.003522083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001120151,"about_ca_system_score_gemma":0.001835875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001884492,"about_ca_topic_score_gemma":0.001458601,"domain_scores_codex":[0.999111,0.0001436921,0.0000859133,0.0001371739,0.0004126724,0.0001095336],"domain_scores_gemma":[0.9978257,0.0002734682,0.0001462612,0.001042729,0.0004484059,0.0002632884],"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":[0.003920327,0.0005184878,0.008315927,0.0007810153,0.0003639652,0.001371021,0.002128427,0.02973475,0.1109094,0.1616731,0.194161,0.4861227],"study_design_scores_gemma":[0.0007256599,0.001232634,0.004181699,0.0002741681,0.0002887043,0.002257837,0.0004671262,0.2912539,0.1139141,0.04939583,0.5356515,0.0003568209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07845873,0.002345882,0.7298414,0.000973843,0.001021332,0.0005701312,0.001294094,0.1532009,0.03229366],"genre_scores_gemma":[0.6761568,0.00130103,0.2581642,0.0009002259,0.0003280432,0.0007119954,0.004659169,0.007690365,0.05008819],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.011704,"threshold_uncertainty_score":0.03915375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01346166295971051,"score_gpt":0.2458760461074057,"score_spread":0.2324143831476951,"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."}}