{"id":"W4388759201","doi":"10.1007/s10518-023-01810-y","title":"Shake table testing of a half-scale stone masonry building aggregate","year":2023,"lang":"en","type":"article","venue":"Bulletin of Earthquake Engineering","topic":"Masonry and Concrete Structural Analysis","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"HORIZON EUROPE Framework Programme; École Polytechnique Fédérale de Lausanne; European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Interlocking; Masonry; Earthquake shaking table; Aggregate (composite); Structural engineering; Full scale; Geology; Geotechnical engineering; Mortar; Intensity (physics); Deformation (meteorology); Engineering; Materials science; Composite material; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002797773,0.0002483968,0.0004575787,0.000247319,0.00004578952,0.0000192589,0.0002291959,0.00009698186,0.0003728932],"category_scores_gemma":[0.0001899663,0.0002660932,0.000142674,0.00100044,0.00003412694,0.00004555624,0.00007587112,0.0002095357,0.00004530095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001603388,"about_ca_system_score_gemma":0.00001015829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009333449,"about_ca_topic_score_gemma":0.00000384888,"domain_scores_codex":[0.9985775,0.00001475416,0.0004833599,0.0002257966,0.0002545694,0.0004440308],"domain_scores_gemma":[0.9992158,0.000225751,0.00008964071,0.000289605,0.00007732048,0.0001018456],"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":[0.000006062727,0.000003463123,0.0006297876,0.0005042031,0.0001181409,0.00001696045,0.0001169785,0.9051523,0.07780048,0.000177077,0.0005721108,0.0149025],"study_design_scores_gemma":[0.0006280024,0.0000947919,0.01622527,0.0007843524,0.0001304327,0.00003301746,0.0001624263,0.8136521,0.1081301,0.00003813492,0.05931249,0.000808929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960738,0.0004592345,0.0009525854,0.00007337685,0.0002148804,0.0001068618,0.000022487,0.00062159,0.001475207],"genre_scores_gemma":[0.9857965,0.00006066513,0.0134779,0.000005981712,0.0001049884,0.00001301279,0.00001162755,0.00005809738,0.0004712864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09150013,"threshold_uncertainty_score":0.9999791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009434987575528232,"score_gpt":0.1916617039681998,"score_spread":0.1822267163926715,"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."}}