{"id":"W4410465682","doi":"10.1016/j.engstruct.2025.120480","title":"A direct derivation method for acceleration and displacement floor response spectra","year":2025,"lang":"en","type":"article","venue":"Engineering Structures","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Korea Institute of Energy Technology Evaluation and Planning; Ministry of Trade, Industry and Energy","keywords":"Acceleration; Displacement (psychology); Spectral line; Structural engineering; Response spectrum; Physics; Mathematics; Geology; Engineering; Classical mechanics; Quantum mechanics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002079783,0.0001839711,0.0001733152,0.0002029634,0.00007575809,0.00005668777,0.00008654135,0.00009429739,0.000005168366],"category_scores_gemma":[0.0001634925,0.0001841266,0.0000317893,0.0001646997,0.000008053606,0.00009323453,0.00002046512,0.000114369,2.196733e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001515706,"about_ca_system_score_gemma":0.00001468972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001154658,"about_ca_topic_score_gemma":8.384204e-7,"domain_scores_codex":[0.9992819,0.00002003102,0.0002043981,0.000186995,0.00008164396,0.0002249835],"domain_scores_gemma":[0.9995258,0.0002170168,0.0000187407,0.0001671878,0.00002756808,0.00004362577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007487507,0.00000932907,0.0002317544,0.002594586,0.0002843938,0.000003927264,0.001134713,0.40182,0.3996524,0.02944891,0.005317403,0.1587538],"study_design_scores_gemma":[0.0006017252,0.0000914327,0.1707184,0.0001420768,0.00004365267,0.000007542598,0.00002414005,0.2829538,0.5301651,0.003859069,0.01096634,0.0004266469],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3567002,0.0004492567,0.6402506,0.0001425123,0.0008826106,0.0005074959,0.0000137025,0.0009895995,0.00006407227],"genre_scores_gemma":[0.7090678,0.00002553176,0.290543,0.00002912554,0.0001275876,0.000130551,0.000008256141,0.00002828706,0.00003982927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3523677,"threshold_uncertainty_score":0.7508464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009649000678844765,"score_gpt":0.3075820201906656,"score_spread":0.2979330195118208,"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."}}