{"id":"W2955645019","doi":"10.48550/arxiv.1906.11175","title":"FPGA-based Multi-Chip Module for High-Performance Computing","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Field-programmable gate array; Computer science; Embedded system; Chip; Computer architecture; Operating system; Computer hardware; Reconfigurable computing; Telecommunications","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":[0.0001327784,0.0002655638,0.0001757838,0.0003002263,0.0001329802,0.00032931,0.0005529394,0.0002239365,0.01928498],"category_scores_gemma":[0.0001748213,0.0001039179,0.0001291254,0.0002599925,0.00008319664,0.0003338489,0.0002796564,0.0002798911,0.003827819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002749421,"about_ca_system_score_gemma":0.0002085772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003794679,"about_ca_topic_score_gemma":0.0007836157,"domain_scores_codex":[0.9998935,0.0000209316,0.000005390175,0.00002259814,0.00003642169,0.00002102984],"domain_scores_gemma":[0.9999075,0.000012925,0.000007605177,0.00003897222,0.00002252237,0.0000105019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008754776,0.0002399909,0.003801049,0.0007575482,0.0001871962,0.0007120006,0.0001593412,0.01753845,0.3898713,0.03865454,0.0557239,0.4914792],"study_design_scores_gemma":[0.0002705872,0.001857183,0.01658347,0.0001517971,0.000164006,0.001939625,0.00009227451,0.1634973,0.3650684,0.006841119,0.4434471,0.00008715429],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2592636,0.00510666,0.5603586,0.0005034649,0.0006828104,0.0006477556,0.002422574,0.02589895,0.1451156],"genre_scores_gemma":[0.7938034,0.0007104662,0.1672198,0.0003331112,0.00006726199,0.0002245122,0.001869788,0.0002838084,0.03548787],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01928498,"threshold_uncertainty_score":0.06451464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09114224604998085,"score_gpt":0.2085742147762647,"score_spread":0.1174319687262838,"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."}}