{"id":"W4252821966","doi":"10.2139/ssrn.3350140","title":"Convergence of a Robust Price Driven Co-ordination Algorithm for Large-Scale, Worse-Case Scenario, Linear Quadratic Optimization Problems","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Convergence (economics); Quadratic equation; Scale (ratio); Ordination; Mathematical optimization; Algorithm; Mathematics; Quadratic model; Computer science; Economics; Statistics","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":[0.003565823,0.001325916,0.002007812,0.0008892099,0.0006652422,0.001705792,0.002468383,0.00272874,0.003649078],"category_scores_gemma":[0.01011274,0.0008558007,0.0007380993,0.001000629,0.001310248,0.001280366,0.002569,0.002115476,0.0006323276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001268877,"about_ca_system_score_gemma":0.003104153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007302042,"about_ca_topic_score_gemma":0.00457533,"domain_scores_codex":[0.9989756,0.0004320859,0.00005035068,0.0001816105,0.0002280273,0.0001322837],"domain_scores_gemma":[0.9951959,0.003055007,0.000425042,0.0002688844,0.0008014147,0.0002536692],"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":[0.0001160297,0.0000517336,0.0002115921,0.00004119911,0.00002938721,0.00002419586,0.0000246294,0.9823926,0.0004966537,0.003773184,0.0007819101,0.012057],"study_design_scores_gemma":[0.00001113388,0.00001544879,0.00002354919,0.000002102015,0.000001705021,0.000003580159,0.000002569979,0.9990911,0.00007743818,0.0006851669,0.00008407214,0.000002042751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02482671,0.0002316826,0.9703912,0.0003138782,0.00008441346,0.0001048706,0.00006287066,0.000341505,0.003642871],"genre_scores_gemma":[0.620775,0.0001742116,0.3735333,0.0002666094,0.0001057944,0.0003882753,0.0002562887,0.0003472703,0.004153178],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007302042,"threshold_uncertainty_score":0.01885808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007762850865119251,"score_gpt":0.2247651702422932,"score_spread":0.2170023193771739,"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."}}