{"id":"W2951116686","doi":"10.1002/net.21892","title":"Monotonicity and conformality in multicommodity network‐flow problems","year":2019,"lang":"en","type":"article","venue":"Networks","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"General Motors Foundation","keywords":"Monotonic function; Convexity; Multi-commodity flow problem; Mathematics; Flow network; Mathematical optimization; Graph; Regular polygon; Flow (mathematics); Directed graph; Computation; Convex function; Discrete mathematics; Combinatorics; Algorithm","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":[0.001098576,0.0002248466,0.0003001239,0.0001277299,0.0001081114,0.0002783654,0.0002490605,0.0001278626,0.0002341222],"category_scores_gemma":[0.00003110278,0.0002220561,0.00004957619,0.0004784496,0.00005451917,0.0009407902,0.0005545081,0.000328051,0.00009142847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007984802,"about_ca_system_score_gemma":0.00001092172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00125865,"about_ca_topic_score_gemma":0.0006529164,"domain_scores_codex":[0.9983773,0.00002385914,0.0003393912,0.0003800766,0.000196531,0.0006828177],"domain_scores_gemma":[0.9992965,0.0000730599,0.000160209,0.0003779714,0.00007295604,0.00001923199],"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":[0.00003963225,0.00004697111,0.409367,0.0002260521,0.00001529121,0.0000081735,0.00003250039,0.5705678,5.082626e-7,0.007809032,0.002953403,0.008933601],"study_design_scores_gemma":[0.0009368398,0.000006845343,0.1239295,0.00004906669,0.00001344343,4.37914e-7,0.0001369461,0.8129677,1.843427e-7,0.002314925,0.05940976,0.0002343635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9314712,0.000530153,0.006781776,0.001030957,0.001203916,0.002964239,0.000001184365,0.0003152057,0.05570138],"genre_scores_gemma":[0.996364,0.00003154508,0.0002851519,0.002119145,0.0007326536,0.00006155542,0.00003144924,0.00002673906,0.0003477413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2854375,"threshold_uncertainty_score":0.9055187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007329042674740536,"score_gpt":0.1898088581834141,"score_spread":0.1824798155086735,"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."}}