{"id":"W4412656413","doi":"10.1080/15732479.2025.2531397","title":"Improvements in forecasting and normalizing limited displacement responses of long-span steel bridges subjected to seasonal temperature variability","year":2025,"lang":"en","type":"article","venue":"Structure and Infrastructure Engineering","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mitacs","funders":"European Space Agency","keywords":"Span (engineering); Displacement (psychology); Structural engineering; Engineering; Environmental science; Forensic engineering; Psychology","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":[0.0004734387,0.0007763196,0.0003509175,0.0003259426,0.0001592919,0.0002870387,0.0003206448,0.0004477096,0.0003999627],"category_scores_gemma":[0.001103501,0.0001697186,0.000476438,0.0002968031,0.0001183091,0.0005588148,0.0002922166,0.0005819895,0.000225486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001518955,"about_ca_system_score_gemma":0.0003038429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003123299,"about_ca_topic_score_gemma":0.005307131,"domain_scores_codex":[0.9998829,0.00002061624,0.000006739024,0.0000419255,0.00003244658,0.00001532969],"domain_scores_gemma":[0.9997777,0.00007102545,0.00003456137,0.00003649089,0.00006879199,0.00001143839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00009473388,0.0001707519,0.01157428,0.00004705916,0.00007759699,0.00009127321,0.00009861141,0.706394,0.05358209,0.0006826003,0.001019538,0.2261674],"study_design_scores_gemma":[0.000001214728,0.00002766903,0.003322411,0.000002341525,0.000007748062,0.000009850624,0.00001081363,0.9922563,0.00407713,0.0001078277,0.000171077,0.000005617938],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4942323,0.0003418858,0.502227,0.0001579007,0.0001013266,0.00002985274,0.0001773589,0.001017575,0.001714844],"genre_scores_gemma":[0.9492977,0.000151876,0.04894712,0.00002290416,0.00002894299,0.00002254465,0.0003643931,0.00004699027,0.001117497],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003123299,"threshold_uncertainty_score":0.006210268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006013297501122363,"score_gpt":0.2382702631019937,"score_spread":0.2322569656008713,"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."}}