{"id":"W2954878952","doi":"10.29173/mocs96","title":"Lateral Performance of Cross-laminated Timber Shear Walls: Analytical and Numerical Investigations","year":2019,"lang":"en","type":"article","venue":"Modular and Offsite Construction (MOC) Summit Proceedings","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"FPInnovations; University of Northern British Columbia","funders":"","keywords":"Cross laminated timber; Shear wall; Structural engineering; Parametric statistics; Shear (geology); Finite element method; Kinematics; Engineering; Geotechnical engineering; Geology; Mathematics; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00006483772,0.0001680839,0.0002291968,0.0001088399,0.00008106553,0.00009583192,0.00004818917,0.0001066598,0.0000794941],"category_scores_gemma":[0.000009210647,0.0001483833,0.0000368197,0.0001788505,0.0002336856,0.0005031303,0.00003161604,0.0001331806,0.000019565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002315948,"about_ca_system_score_gemma":0.000008597197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001077858,"about_ca_topic_score_gemma":4.708811e-7,"domain_scores_codex":[0.9992433,0.000004331317,0.000229936,0.0002082939,0.0001274564,0.0001866631],"domain_scores_gemma":[0.9996887,0.00001041866,0.00003725007,0.00006666389,0.0001058454,0.00009112666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003655491,0.00001386674,0.9905417,0.0003053767,0.00009121965,8.284783e-7,0.0003304382,0.0005410236,0.003741295,0.001051055,0.00008267262,0.003263958],"study_design_scores_gemma":[0.001483933,0.0003208648,0.3528448,0.0001903785,0.0001315811,0.00008703287,0.0002151691,0.6141189,0.02652049,0.0002550563,0.003315844,0.0005160296],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972942,0.0002532671,0.0000453719,0.0000501152,0.000117812,0.0001520965,0.000006606114,0.0001087076,0.001971793],"genre_scores_gemma":[0.9974838,0.00009548845,0.001806272,0.00001436635,0.00003434134,0.00000739251,0.00001126116,0.00001972626,0.0005273771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6376969,"threshold_uncertainty_score":0.6050896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008290284863517447,"score_gpt":0.2006977100613977,"score_spread":0.1924074251978803,"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."}}