{"id":"W2155560344","doi":"10.1109/mnrc.2008.4683373","title":"A spatial computing architecture for implementing computational circuits","year":2008,"lang":"en","type":"article","venue":"","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Computer architecture; Scalability; Debugging; Field-programmable gate array; Electronic circuit; Computer engineering; Design flow; Encoding (memory); Benchmark (surveying); Architecture; Parallel computing; Embedded system; Artificial intelligence; Engineering; Programming language","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":[0.000258206,0.0004419943,0.000212502,0.0006452549,0.0007052378,0.001170465,0.001332637,0.0005308758,0.008322419],"category_scores_gemma":[0.0007449597,0.0002519812,0.0004100236,0.000961228,0.0006963342,0.001288893,0.0005327518,0.0006674404,0.002111492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008106484,"about_ca_system_score_gemma":0.001196972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003663009,"about_ca_topic_score_gemma":0.00516994,"domain_scores_codex":[0.9997535,0.00004691902,0.00002213522,0.00004046714,0.0001017854,0.00003510026],"domain_scores_gemma":[0.9996444,0.00007971956,0.00002066222,0.0001167865,0.0001215739,0.00001694219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002389935,0.00009903467,0.001352447,0.0003765227,0.00005334725,0.0002739016,0.0002178294,0.07987761,0.05908235,0.496316,0.0186477,0.3434644],"study_design_scores_gemma":[0.0001224547,0.0004957913,0.0008060655,0.0001210216,0.0001279726,0.0006587149,0.0001192745,0.5220763,0.1014385,0.1175248,0.2564386,0.00007063179],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01427391,0.0007297432,0.9477329,0.0004633111,0.0001394554,0.0001036718,0.0001521613,0.00526221,0.03114266],"genre_scores_gemma":[0.1971296,0.0008140206,0.7862977,0.000428068,0.00007380638,0.000235949,0.0003268201,0.0001845725,0.01450939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008322419,"threshold_uncertainty_score":0.02784127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02226323323460227,"score_gpt":0.2434914988902556,"score_spread":0.2212282656556533,"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."}}