{"id":"W1965251166","doi":"10.1061/(asce)em.1943-7889.0000812","title":"Damage/Deterioration Detection for Steel Structures Using Distributed Fiber Optic Strain Sensors","year":2014,"lang":"en","type":"article","venue":"Journal of Engineering Mechanics","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Fiber optic sensor; Optical fiber; Reduction (mathematics); Cracking; Strain (injury); Strain gauge; Finite element method; Tension (geology); Fiber; Composite material; Structural engineering; Computer science; Engineering; Ultimate tensile strength","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002791805,0.0002197041,0.0002951456,0.0001938909,0.00004718871,0.00004992118,0.0001233895,0.0001398119,0.000009043496],"category_scores_gemma":[0.0002959645,0.0002256578,0.0001237795,0.0001762423,0.0000054046,0.0002715228,0.00001150433,0.0002774845,0.000001321167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002050636,"about_ca_system_score_gemma":0.00001261143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.663345e-7,"about_ca_topic_score_gemma":5.632626e-7,"domain_scores_codex":[0.9989159,0.0000169277,0.0004806457,0.0001118801,0.0002005926,0.0002741324],"domain_scores_gemma":[0.9992673,0.0001290752,0.0001642436,0.0001647674,0.0001659746,0.0001085988],"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":[0.00001060437,0.000002890953,2.582014e-7,0.00006058665,0.00003823619,0.000002891841,0.00003540836,0.7137376,0.2842925,0.0003356394,0.000004723237,0.001478736],"study_design_scores_gemma":[0.0004762163,0.0001389276,0.0000598193,0.0000589614,0.00007079951,0.0001374384,0.0000479638,0.964716,0.03267016,0.0006300359,0.0007692285,0.0002244583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3889403,0.00003029635,0.6101027,0.000004411196,0.000726092,0.00009662211,0.00002087302,0.00007573279,0.000003000002],"genre_scores_gemma":[0.8471566,0.000006025751,0.1523748,0.000003662089,0.0003639566,0.000002423917,0.000007214908,0.00007915201,0.000006133987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4582162,"threshold_uncertainty_score":0.9202056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01169985813926526,"score_gpt":0.2221151765561465,"score_spread":0.2104153184168812,"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."}}