{"id":"W2128228429","doi":"10.1021/ie0341000","title":"Nonlinear Optimization with Many Degrees of Freedom in Process Engineering","year":2004,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Honeywell (Canada)","funders":"Carnegie Mellon University","keywords":"Degrees of freedom (physics and chemistry); Robustness (evolution); Nonlinear system; Computer science; Nonlinear programming; Mathematical optimization; Process (computing); Convergence (economics); Interior point method; Point (geometry); Algorithm; Mathematics","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":[0.0008185363,0.0006453269,0.0005979298,0.0003255277,0.0004030064,0.0008185613,0.0003594682,0.0008476768,0.001121422],"category_scores_gemma":[0.001707314,0.0003593493,0.0004382749,0.0008519138,0.001362058,0.001028854,0.00103103,0.001397614,0.0002850346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004331706,"about_ca_system_score_gemma":0.0005595397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001492713,"about_ca_topic_score_gemma":0.001395904,"domain_scores_codex":[0.9996456,0.000171323,0.000009810077,0.00004356329,0.0001135775,0.00001623729],"domain_scores_gemma":[0.9995271,0.0003476605,0.00004114411,0.00003254801,0.00003933805,0.00001229702],"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":[0.0000435289,0.00004291016,0.0003572095,0.0001648797,0.00002098146,0.00007232258,0.00004664548,0.8444409,0.003454402,0.1070558,0.001012716,0.04328752],"study_design_scores_gemma":[0.000008539174,0.00002486463,0.0001113832,0.000013139,0.00000482903,0.00002271636,0.000007857014,0.9424523,0.0007606701,0.05374981,0.002833176,0.00001073754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02773702,0.007773974,0.9483376,0.0009658744,0.000168979,0.00003310103,0.00003444139,0.000105856,0.01484325],"genre_scores_gemma":[0.5818909,0.00886221,0.3989027,0.0002940459,0.0004279391,0.0001615611,0.00009346643,0.0001144266,0.009252732],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001492713,"threshold_uncertainty_score":0.004328907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09377246056000574,"score_gpt":0.3684465583282857,"score_spread":0.27467409776828,"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."}}