{"id":"W2002576503","doi":"10.1016/j.disopt.2005.03.001","title":"A semidefinite optimization approach for the single-row layout problem with unequal dimensions","year":2005,"lang":"en","type":"article","venue":"Discrete Optimization","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":153,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Semidefinite programming; Mathematical optimization; Relaxation (psychology); Mathematics; Heuristic; Upper and lower bounds; Linear programming; Linear programming relaxation; Simple (philosophy); Matrix (chemical analysis); Space (punctuation); Facility location problem; Computer science","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":[0.001569336,0.001491982,0.001455955,0.0005713083,0.0004002164,0.001433069,0.001830219,0.001510575,0.009667464],"category_scores_gemma":[0.004097955,0.001084273,0.001065609,0.001074355,0.0009411802,0.001929249,0.001526289,0.002638301,0.001489313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008026524,"about_ca_system_score_gemma":0.001277783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001976007,"about_ca_topic_score_gemma":0.002900917,"domain_scores_codex":[0.9991946,0.0003703532,0.00002351298,0.0001145724,0.0002453293,0.00005163415],"domain_scores_gemma":[0.9980884,0.001333832,0.0001118827,0.000127647,0.0002541741,0.00008413808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005465229,0.0001077539,0.0001050471,0.0001843541,0.00003690205,0.00007894065,0.00004740477,0.9037552,0.001921805,0.06256823,0.006205867,0.0249339],"study_design_scores_gemma":[0.0000101181,0.00001746093,0.00001736545,0.000006243077,0.000003857238,0.00001716434,0.000007037665,0.9877183,0.0001728857,0.01118734,0.0008376126,0.000004549639],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001271377,0.0000781031,0.995801,0.0001274487,0.00003120913,0.00002057516,0.00006663606,0.00007283399,0.00253083],"genre_scores_gemma":[0.1412568,0.0005245837,0.8441227,0.0003427749,0.0001717976,0.0004057022,0.0005418108,0.0004506798,0.01218321],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009667464,"threshold_uncertainty_score":0.03234088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01482290958933528,"score_gpt":0.2092666094721759,"score_spread":0.1944436998828406,"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."}}