{"id":"W2607511250","doi":"10.1117/12.2260122","title":"Evaluation of truss bridges using distributed strain measurements","year":2017,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Truss; Structural engineering; Strain gauge; Truss bridge; Bridge (graph theory); Bending; Computer science; Structural health monitoring; Optical fiber; Fiber Bragg grating; Connection (principal bundle); Span (engineering); Engineering; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007001297,0.000720734,0.0003164831,0.001150751,0.0002876502,0.0003539958,0.0008930014,0.0006481329,0.0009601882],"category_scores_gemma":[0.001132757,0.0002581068,0.0002527816,0.0006867789,0.0003410802,0.0005690432,0.0004373075,0.0003683457,0.0003152009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003070971,"about_ca_system_score_gemma":0.0002002371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00131391,"about_ca_topic_score_gemma":0.004626522,"domain_scores_codex":[0.999027,0.00006110459,0.00003939197,0.000178823,0.0006387552,0.00005498833],"domain_scores_gemma":[0.9990933,0.0001303709,0.0001362585,0.0001171046,0.0004739265,0.00004903844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002953104,0.0005947287,0.02927834,0.0001947468,0.00005211484,0.0001979852,0.0003808833,0.02202242,0.8756825,0.0002843894,0.0002798119,0.07073674],"study_design_scores_gemma":[0.00004805849,0.00464659,0.1395917,0.00004414841,0.00007386927,0.0005718162,0.0005602912,0.1632486,0.6890683,0.0002798901,0.001792969,0.00007379577],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9771248,0.0001402321,0.0209456,0.00001572522,0.00001992896,0.00004745278,0.0001647996,0.0001598978,0.001381588],"genre_scores_gemma":[0.9884697,0.0001235953,0.01034459,0.0000147474,0.000004940514,0.00003724673,0.000168242,0.00001722356,0.0008197197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00131391,"threshold_uncertainty_score":0.0037027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04809392070693413,"score_gpt":0.2843957827384736,"score_spread":0.2363018620315395,"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."}}