{"id":"W4281285597","doi":"10.1007/978-981-19-1004-3_37","title":"Hygrothermal Analysis of Cross-Laminated Timber (CLT) in Canadian Climates With and Without Adhesive Layers Using a 1D-HAM Numerical Modelling Tool","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Adhesive; Cross laminated timber; Moisture; Materials science; Composite material; Layer (electronics); Environmental science; Structural engineering; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001156664,0.0005273037,0.0008272284,0.001266764,0.00004693683,0.00005215137,0.0001286632,0.0002849602,0.0002858694],"category_scores_gemma":[0.00001790925,0.0005036613,0.0001142684,0.0004192899,0.00004613406,0.0001377385,0.0000368838,0.0006273527,9.159953e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005433776,"about_ca_system_score_gemma":0.00007528924,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01771035,"about_ca_topic_score_gemma":0.08316398,"domain_scores_codex":[0.9984871,0.00001187269,0.0004089045,0.0003633019,0.0002086483,0.0005201807],"domain_scores_gemma":[0.9994462,0.0001165261,0.00006616487,0.00023533,0.00003517607,0.0001006774],"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":[0.00003140282,0.000005174181,0.01681288,0.0001849887,0.0008196429,0.00006818001,0.0007253157,0.9809639,0.0001367712,0.00009019292,2.29508e-7,0.0001613366],"study_design_scores_gemma":[0.0003630942,0.00004947411,0.0006383073,0.0003049315,0.000446796,0.00001282676,0.000004599538,0.9969303,0.0003905188,0.00003873411,0.0002500805,0.0005703595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9055158,0.008604359,0.06989177,0.00002878679,0.0002640657,0.001187453,0.000326588,0.0003923102,0.01378885],"genre_scores_gemma":[0.9969627,0.0001262293,0.002484056,0.000009858174,0.00002934548,0.00002825564,0.00006980405,0.000172242,0.0001174774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09144691,"threshold_uncertainty_score":0.9997415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01339085081245377,"score_gpt":0.2136456231148451,"score_spread":0.2002547723023913,"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."}}