{"id":"W131653378","doi":"","title":"Condition Assessment of Concrete Bridge Decks using Ground Penetrating Radar","year":2014,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bridge (graph theory); Ground-penetrating radar; Rebar; Engineering; Visual inspection; Bridge deck; Nondestructive testing; Forensic engineering; Structural health monitoring; Bridge maintenance; Structural engineering; Corrosion; Deck; Civil engineering; Radar; Computer science; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004582583,0.0002740422,0.0004745761,0.0005671356,0.0004288559,0.00009130483,0.0004513724,0.0002883575,0.00003162539],"category_scores_gemma":[0.00002885612,0.0003411438,0.0002029448,0.0007495402,0.0001628977,0.0001897133,0.00005571204,0.0009852363,0.000008904214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005391305,"about_ca_system_score_gemma":0.0003811002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004925993,"about_ca_topic_score_gemma":0.0007297634,"domain_scores_codex":[0.9977136,0.0003991873,0.0003537866,0.000438219,0.0005983203,0.0004969116],"domain_scores_gemma":[0.9985012,0.0003513292,0.000189912,0.0004908697,0.0002632277,0.0002034589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004312077,0.00002553275,0.00235028,0.000909018,0.000258647,0.00007443071,0.000144742,0.0001207513,0.9772816,0.01787124,0.0002076123,0.0007130193],"study_design_scores_gemma":[0.00105198,0.0003441041,0.9177024,0.000701441,0.0003088892,0.00001823003,0.001536589,0.008408564,0.05971158,0.00217855,0.006967721,0.001069973],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9036294,0.00005476704,0.001316999,0.000008667433,0.0004941756,0.0004311153,0.00002775963,0.0001085534,0.09392856],"genre_scores_gemma":[0.9955906,0.00004911618,0.001187873,0.000001332635,0.0003216264,0.00000555832,0.0002384327,0.00006227577,0.0025432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9175701,"threshold_uncertainty_score":0.999904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03659678220151195,"score_gpt":0.3330057444022791,"score_spread":0.2964089622007671,"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."}}