{"id":"W4210273991","doi":"10.1155/2022/7783588","title":"An Overview of Pavement Degradation Prediction Models","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pavement management; Pavement engineering; Predictive modelling; International Roughness Index; Performance prediction; Computer science; Engineering; Asphalt pavement; Process (computing); Transport engineering; Asphalt; Civil engineering; Machine learning; Simulation; Surface finish","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":[0.001069984,0.001652203,0.001131839,0.001783442,0.0004217182,0.001823643,0.002610096,0.001320923,0.002407694],"category_scores_gemma":[0.002125393,0.0006524887,0.00140713,0.002876701,0.0003202274,0.001797653,0.0006900241,0.001798136,0.001512395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009833955,"about_ca_system_score_gemma":0.001011336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01440308,"about_ca_topic_score_gemma":0.005685877,"domain_scores_codex":[0.9993703,0.0001022667,0.00006198416,0.0001860273,0.0002203384,0.0000592723],"domain_scores_gemma":[0.9990049,0.0004718809,0.0001159553,0.00006094901,0.0003206378,0.00002571567],"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":[0.00007432854,0.0001306935,0.006780304,0.0004760486,0.0001772089,0.000131539,0.00006578101,0.7398711,0.001260995,0.01163633,0.005925293,0.2334704],"study_design_scores_gemma":[0.000003640251,0.00004232803,0.001312176,0.00007604586,0.0000504074,0.00006244264,0.00001353337,0.9839903,0.0005365745,0.00515439,0.008736095,0.00002199863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.02223684,0.03884449,0.9159156,0.001342153,0.0004394365,0.0001363026,0.002208176,0.002885828,0.01599111],"genre_scores_gemma":[0.6127937,0.08642052,0.2735288,0.0004633216,0.001410584,0.0006208569,0.00702275,0.0004755389,0.01726397],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01440308,"threshold_uncertainty_score":0.02863848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01808803128142486,"score_gpt":0.2527827857619157,"score_spread":0.2346947544804908,"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."}}