{"id":"W3186633426","doi":"10.1007/s13349-021-00504-w","title":"Distributed monitoring of rail lateral buckling under axial loading","year":2021,"lang":"en","type":"article","venue":"Journal of Civil Structural Health Monitoring","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; York University; Queen's University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Transport Canada","keywords":"Curvature; Deflection (physics); Extrapolation; Structural engineering; Buckling; Boundary value problem; Computer science; Engineering; Geometry; Mathematics; Physics; Mathematical analysis; Optics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001284173,0.000242992,0.0002070817,0.0005211438,0.0001792527,0.0001687481,0.0002991768,0.0004038764,0.001098944],"category_scores_gemma":[0.0003112377,0.00009583794,0.0000726476,0.0002530574,0.0001926672,0.0002630853,0.0002603606,0.0002630276,0.0002275201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002359308,"about_ca_system_score_gemma":0.0001137486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001138427,"about_ca_topic_score_gemma":0.002907328,"domain_scores_codex":[0.9998322,0.00001708887,0.000004309286,0.00003996135,0.00008070882,0.00002582294],"domain_scores_gemma":[0.9996214,0.0001057586,0.00006810053,0.0000270375,0.0001372473,0.00004047688],"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":[0.001093122,0.0002456405,0.03292917,0.0001088969,0.00002911844,0.0002921224,0.0002850782,0.004082671,0.9139968,0.0001298599,0.0005080702,0.04629942],"study_design_scores_gemma":[0.00009315825,0.002146597,0.342492,0.00004427543,0.00008235461,0.001028564,0.0005395123,0.2780129,0.3736378,0.000399005,0.001446147,0.00007760064],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898034,0.00005639368,0.008175739,0.0000318762,0.00001546204,0.00001569155,0.0001299673,0.0001892357,0.001582237],"genre_scores_gemma":[0.9980715,0.00001431717,0.001228212,0.00001546077,0.000005376589,0.000007439631,0.0000303522,0.00000708435,0.0006204087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001138427,"threshold_uncertainty_score":0.003676295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212179489640733,"score_gpt":0.2953010993004133,"score_spread":0.273179304404006,"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."}}