{"id":"W4378878723","doi":"10.1007/978-3-031-32519-9_25","title":"Predicting the Load-Carrying Capacity of Timber-Concrete Notch Connections","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Stiffness; Structural engineering; Finite element method; Simple (philosophy); Carrying capacity; Bearing capacity; Connection (principal bundle); Stress (linguistics); Load bearing; Composite number; Computer science; Engineering; Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002702204,0.0006908215,0.0003580632,0.000629848,0.0002642396,0.00042011,0.0008178385,0.0009004673,0.003141525],"category_scores_gemma":[0.001169945,0.0004916762,0.0003116469,0.0006567917,0.0002314583,0.0006629984,0.0002554237,0.0003572523,0.0009457177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005021189,"about_ca_system_score_gemma":0.0003689013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01525877,"about_ca_topic_score_gemma":0.02034388,"domain_scores_codex":[0.9999143,0.00001417091,0.000003146446,0.0000248598,0.00002905776,0.00001451592],"domain_scores_gemma":[0.9992206,0.0006044114,0.00003795642,0.00003181301,0.00006788516,0.00003723104],"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":[0.00004441589,0.000040028,0.007026262,0.00001804162,0.000006234714,0.00004067937,0.00001162899,0.9715232,0.003043287,0.0003848385,0.0003286562,0.01753277],"study_design_scores_gemma":[0.000001122251,0.00001118503,0.002162815,0.000001662752,0.000001722905,0.000005436726,0.000006666986,0.9966145,0.0008972464,0.0002396182,0.00005516649,0.000002872471],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.943598,0.0002426867,0.04746337,0.00004732452,0.00002234842,0.00002625655,0.0007205943,0.0007405611,0.00713875],"genre_scores_gemma":[0.9910002,0.00008702846,0.006060786,0.000003303503,0.000006869529,0.00001354399,0.0003438601,0.00003667152,0.002447658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01525877,"threshold_uncertainty_score":0.0303399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01927535988513109,"score_gpt":0.1885635467799061,"score_spread":0.169288186894775,"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."}}