{"id":"W4310362706","doi":"10.1080/10298436.2022.2147672","title":"A newly developed hybrid method on pavement maintenance and rehabilitation optimization applying Whale Optimization Algorithm and random forest regression","year":2022,"lang":"en","type":"article","venue":"International Journal of Pavement Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Random forest; International Roughness Index; Algorithm; Mathematical optimization; Metaheuristic; Computer science; Regression; Machine learning; Engineering; Mathematics; Statistics; Surface finish","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0006596923,0.0008184832,0.0009348847,0.0007817217,0.0003460787,0.0006127622,0.00110927,0.001098239,0.001643869],"category_scores_gemma":[0.0009509976,0.0003167656,0.00101754,0.0008227242,0.0002591666,0.0008129865,0.0005236584,0.0006219133,0.0004305171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003520351,"about_ca_system_score_gemma":0.000897684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006071534,"about_ca_topic_score_gemma":0.007360953,"domain_scores_codex":[0.9995709,0.00009412278,0.00002181834,0.0001061973,0.0001664866,0.00004050912],"domain_scores_gemma":[0.9997038,0.0001381235,0.0000348527,0.0000274319,0.00008389167,0.00001192296],"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":[0.00004613305,0.00008334072,0.001020229,0.0001340604,0.000100345,0.00007230802,0.00004055942,0.8037748,0.005801694,0.005441706,0.001235547,0.1822493],"study_design_scores_gemma":[0.000004073674,0.00001519127,0.0001356026,0.000003583954,0.000007485013,0.00001596701,0.000003024034,0.9982856,0.000451569,0.0004653012,0.0006079687,0.00000460769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005494135,0.0001461836,0.9928686,0.0000442917,0.0000287258,0.00002818774,0.00002434092,0.0002237214,0.00114174],"genre_scores_gemma":[0.2799589,0.0003052792,0.7136528,0.000107995,0.00007517452,0.0002932107,0.0002030756,0.0001591885,0.005244335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006071534,"threshold_uncertainty_score":0.01207238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005299996478089937,"score_gpt":0.2318259647399921,"score_spread":0.2265259682619022,"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."}}