{"id":"W2593866979","doi":"10.3846/13923730.2016.1144643","title":"Prediction of axial capacity of piles driven in non-cohesive soils based on neural networks approach","year":2017,"lang":"en","type":"article","venue":"Journal of Civil Engineering and Management","topic":"Geotechnical Engineering and Soil Mechanics","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Pile; Artificial neural network; Perceptron; Structural engineering; Finite element method; Engineering; Multilayer perceptron; Regularization (linguistics); Displacement (psychology); Geotechnical engineering; Computer science; Machine learning; Artificial intelligence","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":[0.0002163486,0.0006307849,0.0003219901,0.0008353012,0.0001544916,0.0003596782,0.0003402549,0.0004473446,0.0006528299],"category_scores_gemma":[0.0008801798,0.0002679415,0.0003119757,0.0004744534,0.0002311886,0.0004456881,0.0002284498,0.0002480501,0.0001616219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003080833,"about_ca_system_score_gemma":0.0003119808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004355357,"about_ca_topic_score_gemma":0.006606297,"domain_scores_codex":[0.9998791,0.00003000464,0.000007300916,0.0000251149,0.00004294,0.00001551895],"domain_scores_gemma":[0.9995822,0.0002342181,0.00007108108,0.00002528149,0.00007207661,0.00001503466],"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":[0.00004834758,0.00003569806,0.003363987,0.00003403173,0.00001427346,0.00005279752,0.00001153714,0.9782804,0.00436517,0.0001915314,0.00006493239,0.0135373],"study_design_scores_gemma":[6.287895e-7,0.0000094457,0.001221966,0.000001442141,0.000002014595,0.000004391561,0.000002972936,0.9975874,0.001056894,0.00008798791,0.00002174228,0.000003032265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7579098,0.0001799851,0.238945,0.00006179769,0.00002077871,0.00004049365,0.000263529,0.0004678455,0.002110731],"genre_scores_gemma":[0.9923075,0.00006334308,0.007037889,0.000003935941,0.000003910249,0.00001963851,0.0001056014,0.00001151964,0.0004466742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004355357,"threshold_uncertainty_score":0.008660018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01155449863990709,"score_gpt":0.1793204821928166,"score_spread":0.1677659835529095,"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."}}