{"id":"W124736584","doi":"10.3141/2522-08","title":"Clustering-Based Threshold Model for Condition Assessment of Concrete Bridge Decks with Ground-Penetrating Radar","year":2015,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Federal Highway Administration","keywords":"Ground-penetrating radar; Rebar; Bridge (graph theory); Reflection (computer programming); Amplitude; Cluster analysis; Structural engineering; Computer science; Slab; Radar; Attenuation; Acoustics; Geology; Geotechnical engineering; Engineering; Artificial intelligence; Telecommunications; Optics; Physics","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":[0.001296807,0.0007858977,0.0009000915,0.0009831481,0.0003908736,0.0009148695,0.001619706,0.00104869,0.001033545],"category_scores_gemma":[0.002772073,0.0004160606,0.0009143492,0.0006975483,0.0005803267,0.000830861,0.0006254241,0.0007123435,0.0003483396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001283475,"about_ca_system_score_gemma":0.0008133783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01906113,"about_ca_topic_score_gemma":0.01075256,"domain_scores_codex":[0.9994953,0.0001256559,0.00003686818,0.0001608787,0.0001042503,0.00007710929],"domain_scores_gemma":[0.9990476,0.0004255368,0.000127075,0.00005787107,0.0003054127,0.00003656885],"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":[0.00007165084,0.00002909237,0.001450429,0.00003183401,0.00003206588,0.00004013855,0.00006227194,0.9808111,0.001787332,0.00196281,0.000213441,0.01350779],"study_design_scores_gemma":[0.000001302847,0.000006993033,0.0003034446,0.000001561968,0.000004038278,0.000005019318,0.000006202662,0.9990829,0.0001829491,0.0003664762,0.00003478693,0.000004247067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09448963,0.0002223133,0.9030678,0.0000914554,0.00002684612,0.0001053423,0.0001380523,0.0005079472,0.00135066],"genre_scores_gemma":[0.9295692,0.000183126,0.06790545,0.00003025528,0.00001878077,0.0001596647,0.0002804024,0.0000474285,0.00180582],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01906113,"threshold_uncertainty_score":0.03790033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.155197235312417,"score_gpt":0.4219115124830393,"score_spread":0.2667142771706222,"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."}}