{"id":"W4392520677","doi":"10.1061/9780784485347.044","title":"Estimating In Situ Shear Wave Velocity Using Machine Learning Techniques","year":2024,"lang":"en","type":"article","venue":"","topic":"Geotechnical Engineering and Soil Mechanics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"WSP (Canada)","funders":"","keywords":"Shear (geology); Computer science; In situ; Geology; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000689378,0.0008622294,0.0004914503,0.001026692,0.0002678526,0.0006867301,0.000817095,0.0008217343,0.0009029799],"category_scores_gemma":[0.002271024,0.0004486105,0.0005749933,0.0008476264,0.0003295477,0.001090052,0.0005257248,0.0008792694,0.0005950304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004419713,"about_ca_system_score_gemma":0.0005950326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005076624,"about_ca_topic_score_gemma":0.006383147,"domain_scores_codex":[0.9996948,0.00005961962,0.00002004942,0.00009256391,0.0001009523,0.00003208028],"domain_scores_gemma":[0.9992023,0.0004331876,0.0001131441,0.00007016922,0.0001562593,0.00002492869],"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":[0.00002683331,0.00005830761,0.004104517,0.00003936038,0.00002808003,0.00003863826,0.00003922798,0.89538,0.007279358,0.0007864084,0.0003416336,0.09187758],"study_design_scores_gemma":[0.000001368841,0.000007631814,0.0004459846,0.000002889272,0.000002036872,0.000006456315,0.000003451949,0.9975151,0.001364121,0.0005083737,0.0001390253,0.000003579642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06959987,0.0001058718,0.9275862,0.0001021185,0.00002378193,0.00002197676,0.0001664647,0.001565425,0.0008283698],"genre_scores_gemma":[0.7606764,0.0001736878,0.2372179,0.00004827274,0.00003837618,0.0000704613,0.0004395377,0.0001031744,0.001232123],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005076624,"threshold_uncertainty_score":0.01009411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01544451963003944,"score_gpt":0.2314635619200974,"score_spread":0.2160190422900579,"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."}}