{"id":"W3151069820","doi":"10.3390/su13074016","title":"Mehar Approach for Finding Shortest Path in Supply Chain Network","year":2021,"lang":"en","type":"article","venue":"Sustainability","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Shortest path problem; Lexicographical order; Mathematical optimization; Interval (graph theory); Pythagorean theorem; Product (mathematics); Computer science; Path (computing); Fuzzy logic; Supply chain; Mathematics; Artificial intelligence; Graph; Theoretical computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008790068,0.00110266,0.00127397,0.002325476,0.001127399,0.001473256,0.001610236,0.001624303,0.00647092],"category_scores_gemma":[0.002414146,0.0005301703,0.001187051,0.003039522,0.000691761,0.0027743,0.001178135,0.001659216,0.000764496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001406099,"about_ca_system_score_gemma":0.00161891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004039545,"about_ca_topic_score_gemma":0.00458406,"domain_scores_codex":[0.9990042,0.0003481689,0.00006327109,0.0002722124,0.0002253638,0.0000869547],"domain_scores_gemma":[0.9991698,0.0005431422,0.00007751617,0.00003395078,0.0001480385,0.00002751952],"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":[0.000111715,0.00007949245,0.0009131272,0.0007324245,0.0001414622,0.0003203145,0.0003309639,0.7219231,0.003095227,0.1029083,0.004107266,0.1653366],"study_design_scores_gemma":[0.00002173101,0.00009666118,0.0001987536,0.0000473678,0.0000284183,0.0001303123,0.0001562318,0.9284281,0.001009562,0.06385407,0.006002293,0.00002644513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006640849,0.000844648,0.9884685,0.0002530307,0.00006173588,0.0001035355,0.0001543279,0.0001324979,0.003340778],"genre_scores_gemma":[0.1569791,0.001801649,0.8328257,0.0001686942,0.0001277129,0.0004054504,0.0005517352,0.00008300979,0.007056905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00647092,"threshold_uncertainty_score":0.02164739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01746343035683275,"score_gpt":0.2177578361489062,"score_spread":0.2002944057920735,"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."}}