{"id":"W2978780371","doi":"10.1016/j.cie.2019.106075","title":"The railway rapid transit network construction scheduling problem","year":2019,"lang":"en","type":"article","venue":"Computers & Industrial Engineering","topic":"Resource-Constrained Project Scheduling","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Ministerio de Economía y Competitividad; Federación Española de Enfermedades Raras","keywords":"Integer programming; Schedule; Scheduling (production processes); Computer science; Mathematical optimization; Revenue; Operations research; Flow network; Profit (economics); Engineering; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004177785,0.0003296968,0.0004793254,0.0002433551,0.0003700742,0.0008897817,0.001181911,0.0002925377,0.00009969563],"category_scores_gemma":[0.0007987046,0.0002425698,0.0002589988,0.001423323,0.000119592,0.0003754454,0.0001797316,0.0009507166,0.0001819322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009240741,"about_ca_system_score_gemma":0.0001693434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001039446,"about_ca_topic_score_gemma":0.000001306269,"domain_scores_codex":[0.9962716,0.0002028738,0.001042407,0.0006608863,0.001057792,0.0007644875],"domain_scores_gemma":[0.995604,0.003011775,0.0002977782,0.0007287253,0.000163601,0.0001941425],"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":[0.00004132044,0.000004637353,0.0009421107,0.000003613026,0.00005173908,0.000003860445,0.0002316609,0.7617831,0.0005055341,0.002238324,0.0003816796,0.2338125],"study_design_scores_gemma":[0.002550306,0.0001651069,0.000291576,0.0002843221,0.00003369333,0.0001287784,0.001037733,0.8719915,0.000792084,0.0008306941,0.1211854,0.000708786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.57956,0.0005383001,0.4019891,0.00131237,0.01266177,0.001473492,0.000005505462,0.0004885932,0.001970909],"genre_scores_gemma":[0.935128,0.00001744227,0.06146348,0.00009532083,0.003070133,0.00002312126,0.000005152617,0.00005784008,0.0001395098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.355568,"threshold_uncertainty_score":0.9891708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05373182046697803,"score_gpt":0.2703974483743323,"score_spread":0.2166656279073543,"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."}}