{"id":"W4412360410","doi":"10.1155/atr/8854907","title":"Network‐Wide Calibration of Link Capacities for Dynamic Traffic Assignment Models","year":2025,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Trafikverket","keywords":"Link (geometry); Calibration; Computer science; Transport engineering; Computer network; Engineering; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001495205,0.0009002811,0.0004870336,0.0009403286,0.0004413874,0.0007451987,0.001155391,0.0007295252,0.00143003],"category_scores_gemma":[0.007275292,0.0005526256,0.0005221358,0.001164561,0.0005379561,0.001405372,0.001213795,0.001883248,0.0003943976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001024596,"about_ca_system_score_gemma":0.001217929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008080293,"about_ca_topic_score_gemma":0.005047727,"domain_scores_codex":[0.9991676,0.0003846865,0.00002670779,0.0001947697,0.0001651497,0.00006106931],"domain_scores_gemma":[0.9980578,0.0009911755,0.0002645113,0.0002923403,0.0003412245,0.00005301745],"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":[0.00001120246,0.00001210275,0.0004854779,0.00001087169,0.00001116215,0.000009319815,0.00001590204,0.9891649,0.0005749867,0.001829391,0.0001765446,0.007698144],"study_design_scores_gemma":[9.955146e-7,0.000003555985,0.0001679283,0.00000235381,0.000001393167,0.00000443191,0.000004525312,0.9979322,0.0003180553,0.001366939,0.000194296,0.000003213883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03795626,0.00007050514,0.959849,0.00006922636,0.00002054184,0.00003475984,0.0001756536,0.000371143,0.001452904],"genre_scores_gemma":[0.8377039,0.0001612359,0.159195,0.00005264511,0.00002685005,0.0002158692,0.001003208,0.0001625808,0.001478646],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008080293,"threshold_uncertainty_score":0.01606655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006346343606604817,"score_gpt":0.2071559414174355,"score_spread":0.2008095978108306,"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."}}