{"id":"W154758769","doi":"10.1007/978-0-387-36594-7_10","title":"Collaborative Event Management in Supply Chains: An Agent-Based Approach","year":2007,"lang":"en","type":"book-chapter","venue":"","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Interdependence; Supply chain; Process management; Plan (archaeology); Context (archaeology); Event (particle physics); Knowledge management; Computer science; Supply chain management; Multi-agent system; Order (exchange); Business; Marketing; Artificial intelligence","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":[0.002108948,0.0007890565,0.001064152,0.000775683,0.001243341,0.004411284,0.003219777,0.002638894,0.0041858],"category_scores_gemma":[0.003592292,0.0007285244,0.001005989,0.002095194,0.001299388,0.004854721,0.002056234,0.001989734,0.0007350907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000861976,"about_ca_system_score_gemma":0.0009404831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001627546,"about_ca_topic_score_gemma":0.001321101,"domain_scores_codex":[0.9984071,0.0006765213,0.0001225955,0.0002585098,0.0004402099,0.00009502502],"domain_scores_gemma":[0.9984807,0.001072779,0.0001089691,0.0001435012,0.0001175099,0.00007665464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001541342,0.0002499012,0.0004253754,0.0005226409,0.0001849278,0.000374643,0.001113638,0.2471093,0.004359752,0.4896051,0.007377968,0.2485226],"study_design_scores_gemma":[0.00005754262,0.00008472378,0.0001978381,0.0001090224,0.0001046945,0.0002299954,0.0003358937,0.6872589,0.00323983,0.2683987,0.03993206,0.00005090813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003492338,0.002812471,0.978243,0.0005170376,0.0001510315,0.00008258223,0.00002697693,0.0002252824,0.01444937],"genre_scores_gemma":[0.3277749,0.006994094,0.642312,0.0002108375,0.0004982405,0.0003178254,0.0001739889,0.0001299451,0.02158821],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004411284,"threshold_uncertainty_score":0.01400286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03693969740185067,"score_gpt":0.2779887026660136,"score_spread":0.241049005264163,"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."}}