{"id":"W4383093065","doi":"10.1139/cgj-2022-0598","title":"Hierarchical Bayesian model for predicting small-strain stiffness of sand","year":2023,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Geotechnical Engineering and Soil Mechanics","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"Hierarchical database model; Pooling; Computer science; Bayesian probability; Hyperparameter; Data mining; Bayesian hierarchical modeling; Bayesian inference; Mathematics; Algorithm; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003663216,0.0008881709,0.001336599,0.001564789,0.0006068072,0.001084368,0.003106871,0.001523024,0.002587039],"category_scores_gemma":[0.008179259,0.0009960101,0.00121737,0.001391886,0.001019852,0.002124975,0.0009480029,0.001389846,0.0007628225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001456946,"about_ca_system_score_gemma":0.001457271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03248712,"about_ca_topic_score_gemma":0.02965008,"domain_scores_codex":[0.9990509,0.0003788396,0.00004577749,0.0002258841,0.0001910625,0.0001075841],"domain_scores_gemma":[0.9976071,0.001532489,0.000280733,0.0001661069,0.0003370427,0.00007651719],"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":[0.00005700539,0.00002768057,0.002124382,0.00003214063,0.00004844883,0.00004545269,0.0000557766,0.9667417,0.0005730581,0.01468415,0.0006706389,0.01493947],"study_design_scores_gemma":[0.000005911883,0.000007524173,0.0004832324,0.000004463425,0.000007550438,0.000008199409,0.000005094209,0.9922978,0.00007499997,0.006942466,0.0001533301,0.000009413095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05749568,0.0003033083,0.9382499,0.0003177318,0.00002497878,0.00007409068,0.0008176352,0.0004944052,0.002222359],"genre_scores_gemma":[0.8375061,0.0005095114,0.1528758,0.0002110089,0.00007608579,0.0003662203,0.002155248,0.0001478044,0.006152377],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03248712,"threshold_uncertainty_score":0.06459606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0177595578588143,"score_gpt":0.2130496829164905,"score_spread":0.1952901250576762,"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."}}