{"id":"W7152350681","doi":"","title":"Making Up for Lost Time: Strategic infrastructure development for growth and resilience","year":2025,"lang":"en","type":"article","venue":"TSpace","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resilience (materials science); Critical infrastructure; Urban infrastructure; Urban planning; Democracy; Government (linguistics); Strategic planning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001294995,0.0001624233,0.00020238,0.0001150721,0.0001637892,0.00006480535,0.0001390321,0.0001004996,0.00004316153],"category_scores_gemma":[0.00006636344,0.0001506621,0.0000497002,0.0002425878,0.00005361136,0.00008159007,0.00002762396,0.0001027765,0.000003457293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006148187,"about_ca_system_score_gemma":0.00007655859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002847267,"about_ca_topic_score_gemma":0.00001331918,"domain_scores_codex":[0.9992136,0.000009717306,0.0001802289,0.000233612,0.00008380677,0.0002790457],"domain_scores_gemma":[0.9995964,0.0001278148,0.00002584847,0.0001493306,0.00006167198,0.00003889934],"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":[0.0006648889,0.00007383239,0.0102056,0.01107944,0.001421613,0.000007653862,0.01603006,0.484226,0.1907072,0.1173528,0.03479413,0.1334368],"study_design_scores_gemma":[0.003255526,0.0002281736,0.02069796,0.0006565909,0.00046445,0.00001819021,0.007965607,0.6215851,0.2076017,0.09438743,0.04104147,0.002097888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5900727,0.0006160806,0.3963405,0.000419002,0.0003520167,0.0009102736,0.00001709482,0.0002106947,0.01106166],"genre_scores_gemma":[0.9778048,0.00001581394,0.02086026,0.00007858848,0.00004460179,0.00004889743,0.00001023372,0.00001419524,0.001122593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3877321,"threshold_uncertainty_score":0.6143821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.014227856100277,"score_gpt":0.2977376499532115,"score_spread":0.2835097938529345,"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."}}