{"id":"W4386349113","doi":"10.1007/978-3-031-39450-8_18","title":"Simplified Assessment of the in-Plane Seismic Response of Old Brick Masonry Building Aggregates Using DE Macro-Crack Networks","year":2023,"lang":"en","type":"book-chapter","venue":"Rilem bookseries","topic":"Masonry and Concrete Structural Analysis","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Unreinforced masonry building; Masonry; Structural engineering; Fragility; Macro; Parametric statistics; Computer science; Brick; Engineering; Geology; Civil engineering; Mathematics; 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":[0.0003768055,0.0004140991,0.0007533963,0.0001979213,0.00007943762,0.00003335831,0.0003784588,0.0003204833,0.0001270371],"category_scores_gemma":[0.00003272195,0.000352161,0.0003127459,0.0001429503,0.0001700395,0.00008051239,0.0001765659,0.0005060479,0.000001453926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001754701,"about_ca_system_score_gemma":0.00009249798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001373038,"about_ca_topic_score_gemma":0.00006431589,"domain_scores_codex":[0.9983264,0.00007389944,0.0006795546,0.0002770147,0.0002770629,0.0003660553],"domain_scores_gemma":[0.9986761,0.0003635861,0.0003424845,0.0005008877,0.00005800066,0.00005899832],"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":[0.0002377474,0.00000235749,0.0013415,0.0006305326,0.00057498,0.00006393519,0.0003174789,0.9634876,0.01340468,0.01786494,0.0001712635,0.001903031],"study_design_scores_gemma":[0.0007746268,0.0001311795,0.009887236,0.004229641,0.000943399,0.00009666705,0.0002498697,0.9447209,0.01260014,0.01130237,0.01335637,0.001707637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.979196,0.001422698,0.001253677,0.00008159024,0.0007743256,0.0005659982,0.0003228758,0.0002774665,0.01610542],"genre_scores_gemma":[0.9604356,0.0004353096,0.0008807188,0.00003568371,0.0001315715,0.000007420047,0.00002643042,0.0001142309,0.03793307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02182765,"threshold_uncertainty_score":0.999893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0137766151400857,"score_gpt":0.2369598596379965,"score_spread":0.2231832444979108,"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."}}