{"id":"W2108712076","doi":"10.1109/smc.2013.482","title":"Iterative Combinatorial Auction for Carrier Collaboration in Logistics Services","year":2013,"lang":"en","type":"article","venue":"","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Bidding; Combinatorial auction; Computer science; Negotiation; Iterative and incremental development; Auction algorithm; Procurement; Reverse auction; Process (computing); Quality (philosophy); Iterative method; Common value auction; Auction theory; Revenue equivalence; Mathematical optimization; Operations research; Business; Microeconomics; Algorithm; Marketing","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":[0.00343881,0.0008406522,0.001298152,0.0007633425,0.0008643035,0.002059349,0.002717099,0.001315841,0.002503156],"category_scores_gemma":[0.005489545,0.0005176017,0.00137956,0.001291883,0.001345991,0.003184372,0.001372321,0.001287402,0.0003362807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001658581,"about_ca_system_score_gemma":0.002466157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002957044,"about_ca_topic_score_gemma":0.002195972,"domain_scores_codex":[0.9953613,0.002974969,0.0001271914,0.0003168444,0.0008655425,0.0003541271],"domain_scores_gemma":[0.9980732,0.001110352,0.0002267138,0.0002134726,0.000243518,0.0001327285],"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":[0.0001471487,0.0001923109,0.0004729537,0.0001143587,0.0001079037,0.0002653741,0.0001658435,0.8464316,0.002287346,0.1281014,0.0009619786,0.0207519],"study_design_scores_gemma":[0.00002568958,0.00006840585,0.00007584774,0.000005036277,0.00001708801,0.00006109074,0.0000218582,0.9798912,0.0003116669,0.01888454,0.0006223262,0.00001518231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02209989,0.0001549928,0.972843,0.0001199117,0.00002875295,0.0001393857,0.00002701466,0.0001024506,0.004484536],"genre_scores_gemma":[0.8433503,0.000242125,0.1530484,0.00006642195,0.00003011161,0.0002925792,0.00007954558,0.00003547609,0.002855032],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00343881,"threshold_uncertainty_score":0.01818639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05164874489295167,"score_gpt":0.3993493917740757,"score_spread":0.347700646881124,"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."}}