{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004313534,0.0001618351,0.0002517877,0.00003718708,0.00005870218,0.00002504011,0.0001134205,0.0001213661,0.00003293693],"category_scores_gemma":[0.000206173,0.0001741474,0.00009177287,0.0003477979,0.00005475151,0.00006221184,0.00001881935,0.0002085446,5.60718e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004862922,"about_ca_system_score_gemma":0.0001423232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001892487,"about_ca_topic_score_gemma":0.00007432516,"domain_scores_codex":[0.9987623,0.00003128066,0.0002843218,0.000290076,0.0000968253,0.0005351802],"domain_scores_gemma":[0.9993113,0.0001097056,0.00001402404,0.0003224517,0.0001641927,0.00007837916],"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":[0.00003387156,0.0002368342,0.4420779,0.00122558,0.00004062825,0.0001439763,0.0008152763,0.5156711,0.00004104848,0.03427194,0.002530531,0.002911217],"study_design_scores_gemma":[0.00157485,0.00009801589,0.3216695,0.00004842388,0.00007781484,0.00001134003,0.002080248,0.6012684,0.0004748915,0.04926695,0.0223504,0.001079108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2145867,0.002176071,0.7733736,0.0002519415,0.0006019293,0.001773141,0.0001490066,0.0005434778,0.006544102],"genre_scores_gemma":[0.9914256,0.00001959607,0.007817007,0.00002455861,0.0001603554,0.0001235885,0.0001880782,0.00003107157,0.0002101151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7768389,"threshold_uncertainty_score":0.7101525,"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."}}