{"id":"W4385275468","doi":"10.1080/03155986.2023.2229208","title":"Mathematical formulations for multi-period network design with modular capacity adjustments","year":2023,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Modular design; Time horizon; Mathematical optimization; Computer science; Network planning and design; Integer programming; Integer (computer science); Selection (genetic algorithm); Function (biology); Order (exchange); Operations research; Mathematics; Artificial intelligence; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003095274,0.00008768721,0.000124162,0.0002423958,0.00195643,0.0005633026,0.0001016986,0.0001085308,0.00002267005],"category_scores_gemma":[0.0003884137,0.00007262959,0.00002390322,0.0006489729,0.0001450978,0.001776878,0.00001091453,0.0001110767,0.00009105231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007482355,"about_ca_system_score_gemma":0.0003287723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001932224,"about_ca_topic_score_gemma":0.000053601,"domain_scores_codex":[0.9981738,0.0001219375,0.0003930619,0.0001046406,0.0008461418,0.0003603741],"domain_scores_gemma":[0.9982591,0.000363428,0.00007458624,0.00009252207,0.00107536,0.000134949],"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":[0.00005475677,0.00001341452,0.001112566,0.00008005102,0.00002507157,3.914311e-7,0.01506824,0.5465432,0.000003160178,0.4339018,0.002590974,0.0006063291],"study_design_scores_gemma":[0.001069014,0.0001113649,0.007171574,0.0001045011,0.000008804675,0.000002965048,0.007815979,0.9165018,0.00000717259,0.0008188998,0.06621324,0.0001747462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01901942,0.00002411984,0.9744195,0.0005676876,0.0001447785,0.002581254,0.0001173264,0.0001649526,0.002960934],"genre_scores_gemma":[0.9256021,0.00005057082,0.06977694,0.000102309,0.000217922,0.001242951,0.0008778741,0.00001439948,0.002114943],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9065827,"threshold_uncertainty_score":0.9993429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2099483244810672,"score_gpt":0.4028948893331627,"score_spread":0.1929465648520955,"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."}}