{"id":"W2759948479","doi":"10.1080/14680629.2017.1378118","title":"An innovative Primary Surface Profile-based three-dimensional pavement distress data filtering approach for optical instruments and tilted pavement model-related noise reduction","year":2017,"lang":"en","type":"article","venue":"Road Materials and Pavement Design","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Pavement management; Noise reduction; Noise (video); Pavement engineering; Median filter; Computer science; Reduction (mathematics); Filter (signal processing); Reliability (semiconductor); Road surface; Engineering; Reliability engineering; Image processing; Artificial intelligence; Computer vision; Civil engineering; Image (mathematics); Mathematics; Materials science","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":[0.0004866581,0.0006975619,0.0004982188,0.001150424,0.0003324011,0.0007605206,0.0009769975,0.000619386,0.001010624],"category_scores_gemma":[0.001317637,0.0003599685,0.0007052311,0.0008601644,0.0004287539,0.001359909,0.0009146472,0.000708228,0.0005152909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004563829,"about_ca_system_score_gemma":0.0008845949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00362913,"about_ca_topic_score_gemma":0.004841454,"domain_scores_codex":[0.9990197,0.00007624649,0.00005214178,0.0002350717,0.0005473145,0.00006940819],"domain_scores_gemma":[0.9993143,0.00009440748,0.00008412862,0.0001435273,0.0003346014,0.00002908658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002540553,0.0001314196,0.004539508,0.0002441568,0.00007153305,0.0001787245,0.0003375428,0.03199434,0.4171894,0.003143475,0.001646396,0.5402695],"study_design_scores_gemma":[0.00002666859,0.0003316006,0.0113599,0.00002862448,0.0001044206,0.0004731522,0.0001852576,0.6469801,0.3284087,0.002012451,0.009941503,0.0001476462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02149934,0.00008451669,0.9771597,0.00003869253,0.00002197002,0.00004192719,0.00007072397,0.0005970412,0.0004861206],"genre_scores_gemma":[0.3400864,0.0002791543,0.6564934,0.00009539741,0.00003608694,0.0001366258,0.0005037824,0.0001318989,0.00223724],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00362913,"threshold_uncertainty_score":0.007215977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0404975826052527,"score_gpt":0.2604712455008535,"score_spread":0.2199736628956008,"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."}}