{"id":"W1967241189","doi":"10.1002/atr.5670390205","title":"Counting the different efficient paths for transportation networks and its applications","year":2010,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Simple (philosophy); Heuristic; Time complexity; Computer science; Floyd–Warshall algorithm; Mathematical optimization; Flow network; Polynomial; Algorithm; Travel time; Matrix (chemical analysis); Mathematics; Theoretical computer science; Shortest path problem; Graph; Engineering","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":[0.0002616825,0.00008780868,0.0001110369,0.00005628454,0.0001524266,0.00007244517,0.0002870912,0.00002932539,0.000001474138],"category_scores_gemma":[0.000008530004,0.0000603595,0.00006215586,0.0001468978,0.0000174319,0.0004873926,0.000002009264,0.0001609122,2.611523e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006513778,"about_ca_system_score_gemma":0.00001210301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.504362e-7,"about_ca_topic_score_gemma":0.0000303968,"domain_scores_codex":[0.9991897,0.000007706126,0.000352248,0.0001342989,0.0001939042,0.0001221815],"domain_scores_gemma":[0.9991939,0.0001121655,0.0003428678,0.0001246461,0.0001812683,0.00004516009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001048236,0.0003182801,0.001291847,0.0001689383,0.0001003225,0.000009828046,0.003655889,0.3147804,0.01548619,0.2022044,0.0001135391,0.4617656],"study_design_scores_gemma":[0.004029262,0.0004113035,0.5195926,0.0001260287,0.0003079105,0.00001297963,0.0008519643,0.4291914,0.003618918,0.007971358,0.03330741,0.0005788442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2624179,0.000133169,0.7363702,0.0003788725,0.000364597,0.0003047966,0.0000115776,0.00001404302,0.00000479309],"genre_scores_gemma":[0.9822812,0.000109356,0.01729808,0.00006079028,0.0001500887,0.00004000568,0.00004303036,0.000006678803,0.00001078459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7198632,"threshold_uncertainty_score":0.2461389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007085189004296871,"score_gpt":0.2357263435892751,"score_spread":0.2286411545849782,"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."}}