{"id":"W4206894453","doi":"","title":"A reactive decision support system for freight intermodal transportation - a Revenue Management Perspective","year":2018,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Revenue; Perspective (graphical); Revenue management; Business; Traffic management; Decision support system; Transport engineering; Computer science; Operations research; Industrial organization; Finance; Engineering; 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":[0.002047953,0.0007719565,0.0007590269,0.0006878551,0.0008152681,0.003724882,0.001870284,0.001774267,0.009092626],"category_scores_gemma":[0.003638734,0.0003375645,0.000577218,0.0005245146,0.0005882655,0.001640652,0.001059653,0.0009606316,0.001895424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008682648,"about_ca_system_score_gemma":0.001480825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006235955,"about_ca_topic_score_gemma":0.003075725,"domain_scores_codex":[0.9990706,0.0002623011,0.00009638922,0.0002475739,0.000241328,0.00008188884],"domain_scores_gemma":[0.9985056,0.0006659112,0.0001167958,0.0002016805,0.0003515392,0.0001585338],"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":[0.001961615,0.001082206,0.004007875,0.0003882777,0.0002874729,0.00158064,0.0009241301,0.572539,0.07069791,0.04690219,0.01645492,0.2831737],"study_design_scores_gemma":[0.00007728847,0.0001025946,0.0002352475,0.00001493868,0.00004987763,0.0000530214,0.00005024558,0.9826377,0.006163238,0.004989208,0.005604734,0.00002190249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07995071,0.0001425247,0.8902496,0.001061376,0.0002264548,0.0003516149,0.0005769908,0.01848382,0.008956894],"genre_scores_gemma":[0.7913626,0.0001284649,0.1976933,0.0004057473,0.0001096639,0.0002432856,0.0007456173,0.000356818,0.008954672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009092626,"threshold_uncertainty_score":0.03041786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01471737067209064,"score_gpt":0.2340966488001276,"score_spread":0.219379278128037,"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."}}