{"id":"W3112644221","doi":"10.18280/ijsse.100513","title":"An Evaluation Model of Subgrade Stability Based on Artificial Neural Network","year":2020,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Heilongjiang Province; National Natural Science Foundation of China","keywords":"Subgrade; Artificial neural network; Geotechnical engineering; Stability (learning theory); Deformation (meteorology); Subsidence; Structural engineering; Engineering; Computer science; Geology; Artificial intelligence; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000341032,0.0001035456,0.0001653045,0.00006185156,0.00001785593,0.00002136073,0.0001503602,0.00004915204,0.0000124938],"category_scores_gemma":[0.00007699096,0.0001007709,0.00006328792,0.00006485853,0.0000144209,0.0002083642,0.00001103186,0.0002500566,1.450645e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006773031,"about_ca_system_score_gemma":0.00002593018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001382313,"about_ca_topic_score_gemma":0.000001266917,"domain_scores_codex":[0.999025,0.00001728376,0.0003772369,0.00007813127,0.0003872818,0.0001151009],"domain_scores_gemma":[0.9995118,0.0000453563,0.0000793883,0.00005901468,0.0002161131,0.00008830025],"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":[0.0001748562,0.00001110859,0.0002841188,0.00002546,0.00003124759,0.000003480488,0.0005863695,0.9858749,0.009301766,0.0004948601,0.000008498227,0.003203346],"study_design_scores_gemma":[0.0003151764,0.00008154957,0.001168889,0.00005219479,0.00001674606,0.000004402984,0.00004321788,0.9912323,0.006526071,0.0004238726,0.00005126918,0.00008429726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8707371,0.00009678012,0.127695,0.0003081239,0.0009644385,0.00007018004,0.00002077904,0.00003191793,0.00007571892],"genre_scores_gemma":[0.9974567,0.00002666537,0.001693571,0.00005398083,0.000750385,7.604389e-7,0.000005706904,0.00001221596,5.173594e-8],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1267196,"threshold_uncertainty_score":0.4109317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01849107215747118,"score_gpt":0.2379156221888327,"score_spread":0.2194245500313616,"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."}}