{"id":"W1485084509","doi":"10.1109/ictel.2003.1191680","title":"Minimum cost design of a parallel computing cluster","year":2003,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Research Manitoba","funders":"","keywords":"Maxima and minima; Computer science; Mathematical optimization; Approximation algorithm; Function (biology); Linear approximation; Network planning and design; Representation (politics); Approximation error; Function approximation; Linear programming; Process (computing); Algorithm; Artificial neural network; Mathematics; Artificial intelligence; Nonlinear system","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":[0.0004640403,0.00005838765,0.0000904334,0.00005516729,0.00004733992,0.0000524893,0.0002987813,0.00002691816,0.00007297841],"category_scores_gemma":[0.00005498383,0.00004860634,0.00002471496,0.000231664,0.00002508419,0.0001517707,0.00007001002,0.00004765463,0.00004058726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008847255,"about_ca_system_score_gemma":0.00005701299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003494863,"about_ca_topic_score_gemma":6.208684e-7,"domain_scores_codex":[0.9991887,0.0001553736,0.0001742786,0.0001550967,0.000152318,0.0001742192],"domain_scores_gemma":[0.9994452,0.0001376266,0.00004604796,0.0002241504,0.00008442,0.00006255835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007376713,0.0001599546,0.0004773842,0.00002150255,0.000018804,0.000003651004,0.001331197,0.5604911,0.0003834247,0.4171447,0.01104049,0.008920412],"study_design_scores_gemma":[0.0004289542,0.00004517973,0.00003944097,0.00000668901,7.081457e-7,0.00000476059,0.00002104415,0.9959144,0.0005315435,0.001106743,0.001828099,0.00007242894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00007744881,0.00001474603,0.9792417,0.000316929,0.00006553695,0.0002397195,1.049125e-7,0.00005624855,0.01998754],"genre_scores_gemma":[0.187364,0.000005430196,0.8107675,0.0006062128,0.000004462572,0.000003204477,3.141326e-7,0.000003525001,0.001245338],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4354233,"threshold_uncertainty_score":0.1982109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05122015434431328,"score_gpt":0.2831929822788294,"score_spread":0.2319728279345162,"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."}}