{"id":"W4285346953","doi":"10.1109/rsp53691.2021.9806205","title":"Heterogeneous Logic Implementation for Adders in VTR","year":2021,"lang":"en","type":"article","venue":"","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Adder; Verilog; Computer science; Field-programmable gate array; Logic block; Routing (electronic design automation); Block (permutation group theory); Computer architecture; Logic synthesis; Scheme (mathematics); Parallel computing; Logic gate; Critical path method; Design flow; Computer hardware; Embedded system; Engineering; Algorithm","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":[0.0002733433,0.0004454362,0.0003017074,0.0005242262,0.0003266899,0.001288272,0.001056727,0.0002979698,0.005951611],"category_scores_gemma":[0.0005960588,0.0002048584,0.0004758992,0.000536666,0.0002565229,0.001026346,0.0005375122,0.0004105479,0.0008860662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000685012,"about_ca_system_score_gemma":0.0005567272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001204823,"about_ca_topic_score_gemma":0.003932595,"domain_scores_codex":[0.9996442,0.0000528884,0.00003423,0.00007991639,0.0001257457,0.00006309993],"domain_scores_gemma":[0.9997252,0.00006803554,0.00004363145,0.00009063696,0.00005998364,0.00001255232],"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":[0.0007144003,0.000164122,0.001194015,0.0006130269,0.00015153,0.0007821461,0.0002142,0.1534927,0.3546187,0.08498096,0.005208425,0.3978659],"study_design_scores_gemma":[0.0001429437,0.00120997,0.001922218,0.0001211043,0.0002099443,0.001325033,0.0001752836,0.6006123,0.305478,0.03076182,0.05796069,0.00008066334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2074392,0.001771488,0.7488592,0.0002988333,0.0002175806,0.0001850216,0.0005208672,0.004219241,0.03648859],"genre_scores_gemma":[0.7059283,0.0003202925,0.2856247,0.0002066872,0.00003115532,0.00005491926,0.0005041946,0.0002484969,0.007081169],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005951611,"threshold_uncertainty_score":0.01991016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02158370344722339,"score_gpt":0.2881559669677159,"score_spread":0.2665722635204926,"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."}}