{"id":"W2772860561","doi":"","title":"Calibration of MEPDG Performance Models for Flexible Pavement Distresses to Local Conditions of Ontario","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Calibration; Environmental science; Civil engineering; Engineering; Statistics; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006230711,0.0005114312,0.0002709828,0.0002687869,0.0005773437,0.0007319011,0.0009255913,0.0004675867,0.001438646],"category_scores_gemma":[0.001890843,0.0003178962,0.000457513,0.0006143557,0.0003724791,0.0005344508,0.0004339464,0.0004980927,0.0003104009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01064949,"about_ca_system_score_gemma":0.005069776,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9197098,"about_ca_topic_score_gemma":0.913571,"domain_scores_codex":[0.9997323,0.0000339857,0.00001025777,0.00007457731,0.0000815207,0.00006729907],"domain_scores_gemma":[0.9995064,0.00009260501,0.00004473616,0.00006231588,0.0002518367,0.00004214398],"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":[0.0001453593,0.00005073857,0.1017603,0.00004836422,0.00007270764,0.00009162577,0.0002210348,0.8726667,0.001635597,0.001030453,0.002314027,0.01996306],"study_design_scores_gemma":[0.00002930063,0.00003835741,0.1690678,0.00002067223,0.00004199296,0.00002082702,0.000314635,0.8254799,0.001568634,0.0004951802,0.002890136,0.00003250456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774581,0.0001113653,0.01042725,0.0002800476,0.00001562273,0.00003529489,0.003407241,0.0002434651,0.008021677],"genre_scores_gemma":[0.9957866,0.00005005562,0.001138337,0.000008201234,0.00000238252,0.00001084571,0.001310237,0.00002518799,0.001668216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0802902,"threshold_uncertainty_score":0.161526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009343774277356,"score_gpt":0.2346496839241828,"score_spread":0.2245562461814092,"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."}}