{"id":"W4399903363","doi":"10.1016/j.omega.2024.103134","title":"A column and row generation approach to the crowd-shipping problem with transfers","year":2024,"lang":"en","type":"article","venue":"Omega","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Column generation; Column (typography); Computer science; Mathematics; Mathematical optimization; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007635933,0.00005847077,0.00004454059,0.00004856889,0.00005651246,0.00009672016,0.00003240693,0.00002234056,0.000005678426],"category_scores_gemma":[0.000001086065,0.00004277726,0.00001066175,0.0003282769,0.00001390971,0.00008419399,0.000001051988,0.00007587388,0.000005018976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001551831,"about_ca_system_score_gemma":0.00001381708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001098634,"about_ca_topic_score_gemma":0.0002961507,"domain_scores_codex":[0.9996696,0.000004576497,0.00008459517,0.0001019807,0.0000574906,0.00008182343],"domain_scores_gemma":[0.9998732,0.000007743934,0.000002104714,0.00007337193,0.0000168202,0.00002676886],"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":[0.00002250326,0.00008772373,0.001043258,0.001157654,0.0003585585,0.00000787139,0.03742089,0.6202806,0.05191265,0.2000468,0.01351158,0.07414994],"study_design_scores_gemma":[0.001060564,0.0002554299,0.02603173,0.0002315355,0.0001959699,0.00005294679,0.002075257,0.5094635,0.005845108,0.0004045368,0.4534189,0.000964524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6308346,0.0002230445,0.3544535,0.001839522,0.0001349089,0.0006225936,0.0000286809,0.0004450821,0.01141811],"genre_scores_gemma":[0.9961289,0.000008968701,0.003282346,0.0001096632,0.00004803399,0.0001412494,0.00002938767,0.00001424564,0.0002371814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4399073,"threshold_uncertainty_score":0.1744406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0153612375328674,"score_gpt":0.1984403365774681,"score_spread":0.1830790990446007,"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."}}