{"id":"W4415393765","doi":"10.24124/2025/30588","title":"Optimization of pavement maintenance and rehabilitation using pavement management system in Prince George","year":2025,"lang":"","type":"dissertation","venue":"","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pavement management; Asset management; Pavement engineering; Asset (computer security); Mean squared error; Decision support system; Distress; Artificial neural network; Regression analysis; International Roughness Index","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":[0.0005056257,0.0004303261,0.000309626,0.0006730154,0.0006595691,0.001163199,0.000651123,0.0004844003,0.00066779],"category_scores_gemma":[0.001451269,0.0002704034,0.0003299082,0.0007335799,0.0003793144,0.0005479692,0.00059066,0.0004725093,0.0001609612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003939336,"about_ca_system_score_gemma":0.004687712,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4243037,"about_ca_topic_score_gemma":0.6104666,"domain_scores_codex":[0.9997107,0.00006516144,0.00001281469,0.00006017672,0.0000742943,0.00007681372],"domain_scores_gemma":[0.9996018,0.00009042437,0.00006407964,0.00002569021,0.0001646898,0.00005332317],"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":[0.0003102709,0.0002665965,0.1550235,0.00026728,0.0001529639,0.0007821081,0.0006372255,0.6900991,0.01268746,0.002124334,0.002158039,0.1354913],"study_design_scores_gemma":[0.0000233431,0.0003649905,0.1505886,0.0000574955,0.00008746256,0.0001283382,0.001891406,0.8387164,0.004657134,0.0006198947,0.002804635,0.00006018631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867015,0.0001855624,0.01022555,0.0002302632,0.000007146196,0.00007956348,0.0002207135,0.00009526107,0.002254297],"genre_scores_gemma":[0.9930627,0.0001397321,0.005242922,0.00001631884,0.000001350315,0.00002078046,0.0001856212,0.000007213602,0.001323364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5756962,"threshold_uncertainty_score":0.843668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004722337883052779,"score_gpt":0.2231987509280507,"score_spread":0.218476413044998,"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."}}