{"id":"W2100201259","doi":"10.1109/icm.2008.5393533","title":"Placement algorithm for multiplier-based FPGA circuits","year":2008,"lang":"en","type":"article","venue":"","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Field-programmable gate array; Application-specific integrated circuit; Computer science; Routing (electronic design automation); Greedy algorithm; Pipeline (software); Multiplier (economics); Power consumption; Reduction (mathematics); Algorithm; Electronic circuit; Integer programming; Interconnection; Network routing; Power (physics); Embedded system; Mathematics; Telecommunications; Engineering","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":[0.0002388647,0.0006438921,0.0003786837,0.0005967239,0.0004975999,0.0005579729,0.0008540225,0.0006102363,0.005623056],"category_scores_gemma":[0.000626992,0.0003048018,0.0002834807,0.0007016553,0.0002390793,0.0004019829,0.0004563318,0.0003827859,0.001957225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005330472,"about_ca_system_score_gemma":0.0007522883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001359132,"about_ca_topic_score_gemma":0.002375845,"domain_scores_codex":[0.999803,0.00003857923,0.00001509381,0.00003570868,0.00008693681,0.00002074165],"domain_scores_gemma":[0.9998828,0.00002928733,0.00001670573,0.00001591274,0.0000497281,0.000005631663],"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":[0.0001675098,0.00004446971,0.0004426443,0.0001971863,0.000036618,0.0001971226,0.0001265157,0.301525,0.04067896,0.02801258,0.009673124,0.6188982],"study_design_scores_gemma":[0.0000920247,0.0001902745,0.0002911252,0.00002885252,0.0000206213,0.0003345335,0.00004576738,0.9470941,0.01688281,0.01273116,0.02226898,0.00001971087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004770656,0.0001013553,0.9915838,0.00005870738,0.00003950285,0.00008137462,0.00004343872,0.0007201661,0.002601053],"genre_scores_gemma":[0.05978209,0.0001775816,0.9350838,0.00004879956,0.00002971266,0.0001703671,0.0001606976,0.00009684472,0.004449999],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005623056,"threshold_uncertainty_score":0.01881093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02650386566117851,"score_gpt":0.2279425466022554,"score_spread":0.2014386809410769,"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."}}