{"id":"W1972280695","doi":"10.1007/s10479-011-0876-5","title":"The Robust Set Covering Problem with interval data","year":2011,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Regret; Benders' decomposition; Mathematical optimization; Interval (graph theory); Theory of computation; Mathematics; Heuristic; Set (abstract data type); Genetic algorithm; Minimax; Context (archaeology); Algorithm; Heuristics; Computer science; Statistics; 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":[0.002569713,0.00006989946,0.00008888781,0.00009566716,0.0002888222,0.0001116927,0.0006727024,0.00003421288,0.0000758285],"category_scores_gemma":[0.0002557077,0.00004868869,0.00001356661,0.0004413862,0.0001339495,0.0003614649,0.0002295505,0.0002595482,0.00001923809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001038187,"about_ca_system_score_gemma":0.0000678064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001409007,"about_ca_topic_score_gemma":0.0002628482,"domain_scores_codex":[0.9988598,0.0001980241,0.0002107029,0.0001498961,0.0003082326,0.0002733319],"domain_scores_gemma":[0.9985524,0.0001564327,0.000009747456,0.0007404021,0.0004861175,0.0000548337],"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":[0.00002539975,0.00003036002,0.0004568254,0.00004454597,0.00008317834,0.000002704811,0.001592903,0.9822565,0.0005344023,0.002629131,0.005917246,0.006426791],"study_design_scores_gemma":[0.000120691,0.0001008359,0.0006922479,0.00005853547,0.000003545013,0.000005621708,0.000532489,0.9857569,0.009023359,0.00005970777,0.003547104,0.00009895168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2545023,0.00113128,0.6657859,0.002826206,0.0002187104,0.001718136,0.00024512,0.0004511564,0.07312116],"genre_scores_gemma":[0.8115546,0.0004552556,0.1871365,0.00002032234,0.00004965602,0.00004776836,0.00004832796,0.0000424648,0.0006451794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5570522,"threshold_uncertainty_score":0.2221416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5469561555470586,"score_gpt":0.4569992869582814,"score_spread":0.08995686858877716,"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."}}