{"id":"W2951951756","doi":"10.1002/net.20074","title":"An approximation algorithm for Stackelberg network pricing","year":2005,"lang":"en","type":"article","venue":"Networks","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stackelberg competition; Toll; Relaxation (psychology); Linear programming relaxation; Set (abstract data type); Approximation algorithm; Computer science; Constraint (computer-aided design); Flow network; Algorithm; Combinatorics; Mathematics; Mathematical optimization; Linear programming; Mathematical economics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001730634,0.0011713,0.001725883,0.00107371,0.0008407055,0.002417409,0.002662948,0.001941888,0.00844108],"category_scores_gemma":[0.004726711,0.000591989,0.001137417,0.00217599,0.0008290357,0.003588707,0.001474202,0.001921451,0.001314514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002964834,"about_ca_system_score_gemma":0.003664723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008245841,"about_ca_topic_score_gemma":0.007583594,"domain_scores_codex":[0.998743,0.0003548294,0.00005373917,0.0002250081,0.0003011404,0.0003223782],"domain_scores_gemma":[0.9989422,0.0005963882,0.00007148286,0.0001675138,0.0001298041,0.00009265068],"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":[0.0005144628,0.0004649358,0.001010159,0.0001630505,0.0001168876,0.0001121279,0.0002029237,0.7199244,0.001846296,0.09408333,0.0119284,0.169633],"study_design_scores_gemma":[0.00006806335,0.00003315024,0.00005202845,0.000006576621,0.0000136911,0.00002689929,0.00002319585,0.9567018,0.0003570372,0.04166642,0.001045261,0.000005920034],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0706142,0.0005770905,0.9076295,0.001222764,0.0001577286,0.0002655649,0.000464263,0.002163043,0.01690576],"genre_scores_gemma":[0.4819883,0.0004303507,0.5081521,0.0002987579,0.00009909797,0.0003192115,0.001094725,0.0002219437,0.007395553],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00844108,"threshold_uncertainty_score":0.02823824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01407393180372267,"score_gpt":0.2909614343161206,"score_spread":0.276887502512398,"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."}}