{"id":"W4360619528","doi":"10.1061/9780784484685.023","title":"A Deep Learning Model to Predict the Lateral Capacity of Monopiles","year":2023,"lang":"en","type":"article","venue":"","topic":"Geotechnical Engineering and Soil Mechanics","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Artificial neural network; Nonlinear system; Pile; Finite element method; Structural engineering; Convolutional neural network; Computer science; Cone penetration test; Bearing capacity; Engineering; Artificial intelligence; Geotechnical engineering","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":[0.0001858876,0.0005606881,0.0002955457,0.0003238076,0.0001613114,0.0002906019,0.0006930547,0.0006449226,0.00120374],"category_scores_gemma":[0.0004525541,0.0003000159,0.0003305474,0.0002915418,0.0002568293,0.0004736452,0.0003523714,0.0006204362,0.0002622603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005282309,"about_ca_system_score_gemma":0.0007228085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01108799,"about_ca_topic_score_gemma":0.0108541,"domain_scores_codex":[0.9999392,0.000007047372,0.000003093019,0.00001811477,0.00001835546,0.00001412651],"domain_scores_gemma":[0.9998504,0.00004991064,0.00002006566,0.000009313813,0.0000604807,0.000009925154],"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":[0.0000166506,0.00001896115,0.0005489651,0.00001149087,0.000008430748,0.00002584101,0.000005247065,0.9836886,0.00186299,0.0004178304,0.0003061725,0.01308892],"study_design_scores_gemma":[4.47743e-7,0.000003032861,0.00005512383,5.907159e-7,7.919979e-7,0.000001560511,4.343844e-7,0.9996395,0.0001847013,0.00007956507,0.00003341144,7.825051e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1458672,0.0003600871,0.8466876,0.0002938017,0.00006814018,0.00004376625,0.0004909709,0.001036945,0.005151535],"genre_scores_gemma":[0.956875,0.0001458484,0.03734554,0.00009167242,0.0000178649,0.00009871362,0.000414375,0.00003038453,0.004980535],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01108799,"threshold_uncertainty_score":0.02204686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01638806267485931,"score_gpt":0.1939027190463855,"score_spread":0.1775146563715262,"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."}}