{"id":"W4212901485","doi":"10.1109/icaml54311.2021.00033","title":"Software and Hardware Integrated Accelerators for Hadoop Appliance","year":2021,"lang":"en","type":"article","venue":"2021 3rd International Conference on Applied Machine Learning (ICAML)","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Throughput; Scalability; Computer hardware; Field-programmable gate array; Data compression; Lossless compression; Software; Embedded system; Hardware acceleration; Hardware architecture; Computer architecture; Operating system; Wireless","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002179788,0.000287671,0.0002900095,0.0001159945,0.0002922105,0.0006617695,0.0008837523,0.0001152162,0.0005737763],"category_scores_gemma":[0.0001810667,0.0002638433,0.00007394987,0.0002567003,0.00005612857,0.0003044776,0.0006118275,0.0005688053,0.00007162882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006525673,"about_ca_system_score_gemma":0.0001817384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002094211,"about_ca_topic_score_gemma":0.00001263181,"domain_scores_codex":[0.9980031,0.00005619074,0.0003177055,0.0008861591,0.000435587,0.0003012514],"domain_scores_gemma":[0.9986394,0.0001797488,0.000182096,0.0004264601,0.0004237024,0.0001486159],"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":[0.00009824655,0.00013967,0.0007918684,0.00003794118,0.00008664877,0.0000328613,0.0002526492,0.0004028792,0.008999765,0.4312547,0.002274024,0.5556288],"study_design_scores_gemma":[0.001987958,0.0001925844,0.001471215,0.0002365174,0.00001996534,0.00003789208,0.0002119665,0.6469849,0.009547828,0.01317545,0.3253081,0.0008256515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002202908,0.000180335,0.9853449,0.002596195,0.0005909357,0.0002918145,0.0001252926,0.0002312986,0.008436328],"genre_scores_gemma":[0.7595447,0.0003627167,0.2313187,0.001393748,0.0003422054,0.000275374,0.001337266,0.00005471411,0.005370557],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7573418,"threshold_uncertainty_score":0.9999814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03219858722064655,"score_gpt":0.2799681508879874,"score_spread":0.2477695636673409,"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."}}