{"id":"W4234719031","doi":"10.1109/iccad.1990.129896","title":"A global optimization approach for architectural synthesis","year":2002,"lang":"en","type":"article","venue":"","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Polytope; Computer science; Mathematical optimization; Integer programming; Scheduling (production processes); Simplex algorithm; Heuristic; Simplex; Job shop scheduling; Linear programming; Function (biology); Node (physics); Theoretical computer science; Algorithm; Mathematics; Discrete mathematics; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001732149,0.00009881159,0.0001195306,0.00004967941,0.00006264803,0.0001185246,0.0006072738,0.00005337164,0.0000210458],"category_scores_gemma":[0.0000723855,0.00008120252,0.00006643408,0.0002682465,0.00001694062,0.0002196003,0.00006939795,0.00002459891,0.000004694384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005464543,"about_ca_system_score_gemma":0.000006491978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001473301,"about_ca_topic_score_gemma":0.000001048785,"domain_scores_codex":[0.9991553,0.00005520403,0.0001588824,0.0002872886,0.0001460193,0.0001973165],"domain_scores_gemma":[0.9993713,0.0000875964,0.00004867913,0.0003919047,0.00005025664,0.00005024294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001272046,0.0003261994,0.0003903363,0.0001705009,0.00007778109,0.00000523154,0.0008577492,0.1787679,0.0002249029,0.4241233,0.03701954,0.3580237],"study_design_scores_gemma":[0.0000613782,0.00003299163,0.000008064473,0.00000503946,0.000002822935,0.00004000431,0.000005534135,0.9978024,0.0009421934,0.000874456,0.0001118661,0.0001132388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00004323065,0.00003739566,0.9579484,0.0002085439,0.00004183762,0.0004050495,0.000002357391,0.000792917,0.04052024],"genre_scores_gemma":[0.1931306,0.000001100803,0.806223,0.0001002036,0.00003123771,0.0001907256,6.9439e-7,0.000004797557,0.0003176017],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8190345,"threshold_uncertainty_score":0.3311343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03233881047253969,"score_gpt":0.2430899130392005,"score_spread":0.2107511025666608,"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."}}