{"id":"W1606276466","doi":"10.1002/atr.1240","title":"Analytic hierarchy process application in selecting the mode of transport for a logistics company","year":2013,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Analytic hierarchy process; Multiple-criteria decision analysis; Flexibility (engineering); Operations research; Analytic network process; Process (computing); Computer science; Reliability (semiconductor); Function (biology); Mode (computer interface); Hierarchy; Selection (genetic algorithm); Rank (graph theory); Transport engineering; Engineering; Mathematics; Economics","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":[0.001474949,0.0001291741,0.0004551026,0.0004538767,0.00007458625,0.00003981127,0.0005075553,0.00006030532,0.00002297807],"category_scores_gemma":[0.0007973452,0.00008409281,0.000178714,0.00103732,0.00007050374,0.0007475311,0.000001794686,0.0002113078,0.000002050174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004459134,"about_ca_system_score_gemma":0.0001121919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002739385,"about_ca_topic_score_gemma":0.0003029532,"domain_scores_codex":[0.9963934,0.00006236969,0.0020626,0.0002296003,0.001062001,0.0001900247],"domain_scores_gemma":[0.9948677,0.00139265,0.001617854,0.0002428016,0.001814988,0.00006396077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003628808,0.0001195712,0.02550868,0.00004711509,0.00001681818,0.000003427048,0.00542479,0.891042,0.01534021,0.000464568,0.00002095675,0.06164896],"study_design_scores_gemma":[0.002978292,0.0002819916,0.6418853,0.0002166342,0.00009147375,0.00001851878,0.007284791,0.1949383,0.004722803,0.1469253,0.0004015475,0.0002550051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5669471,0.00003786504,0.4323121,0.0001993658,0.00008381954,0.0003918668,0.00001113803,0.000003809595,0.00001296228],"genre_scores_gemma":[0.9734808,0.00001254497,0.02633765,0.0000466844,0.00005115137,0.0000369632,0.000007642614,0.00001309604,0.00001344915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6961038,"threshold_uncertainty_score":0.3429205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0795456967117574,"score_gpt":0.4288961698264365,"score_spread":0.3493504731146791,"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."}}