{"id":"W4297236911","doi":"10.1007/s12061-022-09484-w","title":"Characterizing the Nature of a Multi-Regional Trucking Network Using the Network Robustness Index: An Application to Ontario, Canada","year":2022,"lang":"en","type":"article","venue":"Applied Spatial Analysis and Policy","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Robustness (evolution); Transport engineering; Flow network; Computer science; Truck; Network analysis; Business; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001055982,0.000372605,0.0003880444,0.001849059,0.001713261,0.002016967,0.0009569456,0.0005592443,0.001333783],"category_scores_gemma":[0.006011258,0.0002692378,0.0006203097,0.00404986,0.001076227,0.001039173,0.0007507928,0.0003916066,0.00005791775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02604536,"about_ca_system_score_gemma":0.01276591,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9856726,"about_ca_topic_score_gemma":0.9885312,"domain_scores_codex":[0.9996569,0.00004778544,0.000013323,0.0000771005,0.00008727629,0.0001176392],"domain_scores_gemma":[0.9977975,0.0008846087,0.0003450863,0.0001023048,0.000680831,0.0001897286],"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":[0.0001353418,0.00005095456,0.1632973,0.00007902117,0.0001436553,0.0003831036,0.0005800126,0.801614,0.001487357,0.01362859,0.002745348,0.01585522],"study_design_scores_gemma":[0.00001454598,0.0000228452,0.125933,0.00002310297,0.00006427764,0.00005077956,0.0012072,0.8663339,0.0007233352,0.003874477,0.001707791,0.00004474965],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803005,0.0002410071,0.01050372,0.0004628543,0.000006319183,0.00006520282,0.002319002,0.00007530917,0.006026139],"genre_scores_gemma":[0.9950072,0.0001471325,0.003037213,0.00001415148,0.000002594011,0.00001146144,0.0005095247,0.0000135049,0.00125735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02604536,"threshold_uncertainty_score":0.1889731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007047299542433028,"score_gpt":0.2271237310824441,"score_spread":0.2200764315400111,"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."}}