{"id":"W7017713997","doi":"","title":"Application of Convolutional Neural Network (CNN) Models for Automated Monitoring of Road Pavement and Winter Surface Conditions Using Visual-Spectrum and Thermal Video Cameras","year":2021,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Shandong University","keywords":"Road surface; Convolutional neural network; Visual inspection; Work (physics); Artificial neural network; Snow removal; Data collection; Pavement management","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":[0.0005204265,0.000733883,0.0003273405,0.0006122987,0.0001626074,0.0004698529,0.0007782633,0.0006078138,0.0006911443],"category_scores_gemma":[0.0009163163,0.0002810843,0.0004481921,0.0004734464,0.0001740589,0.000576306,0.0003654762,0.0004543276,0.0002352031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001061034,"about_ca_system_score_gemma":0.000747885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02650829,"about_ca_topic_score_gemma":0.02690532,"domain_scores_codex":[0.9997568,0.00002768699,0.00001288365,0.00007791371,0.00007294807,0.00005179492],"domain_scores_gemma":[0.9996963,0.00006650818,0.0000402666,0.00003139396,0.0001493773,0.00001626322],"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":[0.0002944969,0.0002557097,0.009002548,0.0001370565,0.0002074573,0.0001991625,0.00004873686,0.5921863,0.0463839,0.00147044,0.0027065,0.3471076],"study_design_scores_gemma":[0.000002034893,0.00002155696,0.001072274,0.000003586186,0.00001311347,0.00001153104,0.000003247985,0.9939077,0.004564949,0.0001622476,0.0002335858,0.000004132401],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2785247,0.001195076,0.7095981,0.0003863168,0.0002108344,0.0001394981,0.0005708236,0.0037081,0.005666521],"genre_scores_gemma":[0.9082121,0.0003934606,0.08770072,0.0000985239,0.00002803075,0.00005534438,0.0005147,0.00003854041,0.002958614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02650829,"threshold_uncertainty_score":0.05270803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01127313358741278,"score_gpt":0.2524571195536955,"score_spread":0.2411839859662827,"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."}}