{"id":"W4206915070","doi":"10.5539/mas.v16n1p30","title":"New Approach to Obtain the Maximum Flow in a Network and Optimal Solution for the Transportation Problems","year":2022,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Rajarata University of Sri Lanka","keywords":"Maximum flow problem; Minimum-cost flow problem; Flow network; Out-of-kilter algorithm; Multi-commodity flow problem; Computer science; Mathematical optimization; Flow (mathematics); Heuristic; Algorithm; Mathematics; Theoretical computer science; Graph","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006703438,0.00005982547,0.00005806428,0.00003003415,0.0003701648,0.00006626068,0.0002016348,0.00001167029,0.000005478348],"category_scores_gemma":[0.000006064332,0.00004136917,0.00001204038,0.0004515224,0.00004631788,0.00005248327,0.00002461103,0.00008996158,7.943657e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000405752,"about_ca_system_score_gemma":0.00002302442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006506022,"about_ca_topic_score_gemma":0.00001377905,"domain_scores_codex":[0.9993355,0.000005079371,0.0001101263,0.0001543138,0.0001765183,0.0002185219],"domain_scores_gemma":[0.9997858,0.00004314668,0.00001260379,0.0001068427,0.00000768291,0.00004387294],"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":[0.000005243448,0.000007257556,0.000001604529,0.00001213603,0.000001222467,2.227728e-8,0.002908855,0.950624,0.000636836,0.005998162,0.0001330348,0.03967158],"study_design_scores_gemma":[0.0001587447,0.000007509215,0.00004448589,0.000001877494,0.000004011975,4.947128e-7,0.0002373279,0.991855,0.00001551023,0.006602325,0.001014501,0.00005821606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000714579,0.0000483792,0.9971085,0.0002545155,0.00004359277,0.0009155975,0.000001522613,0.00005416422,0.0008591263],"genre_scores_gemma":[0.7921388,0.000002309483,0.2071155,0.00009065429,0.00001983652,0.0005846336,0.000002946543,0.000009371831,0.00003588804],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7914243,"threshold_uncertainty_score":0.2847046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01929774037166811,"score_gpt":0.2154717108606233,"score_spread":0.1961739704889552,"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."}}