{"id":"W4220711530","doi":"10.18280/mmep.090128","title":"Experimental Study of Soft Clay Soil Improvement by Deep Mixing Method","year":2022,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Geotechnical Engineering and Soil Stabilization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lime; Geotechnical engineering; Pile; Cement; Settlement (finance); Bearing capacity; Mixing (physics); Foundation (evidence); Soil cement; Clay soil; Environmental science; Geology; Materials science; Soil water; Soil science; Composite material; Metallurgy","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":[0.0003906625,0.0002277658,0.0003290049,0.00009448281,0.00009606895,0.00002653543,0.0001403827,0.00005756877,0.00002851928],"category_scores_gemma":[0.00001312481,0.0002381725,0.00005085553,0.0001867591,0.00001094365,0.00005748543,0.0001010413,0.0002904161,0.00000104896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006970237,"about_ca_system_score_gemma":0.000003445744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001894674,"about_ca_topic_score_gemma":1.919038e-7,"domain_scores_codex":[0.9986877,0.00001853132,0.0004568808,0.0002385657,0.000301368,0.0002969923],"domain_scores_gemma":[0.9995428,0.00009624294,0.00003357707,0.0002110172,0.00001688719,0.00009948257],"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":[0.000002546654,0.000316958,0.000001058345,0.0003527371,0.00004073572,7.591377e-7,0.001889375,0.967436,0.02904874,0.0003607947,0.0000111882,0.0005390997],"study_design_scores_gemma":[0.0003775349,0.0003547362,4.285255e-7,0.00003585799,0.00002350732,0.000005899493,0.0005207959,0.9924005,0.005538712,0.000378628,0.0001167988,0.0002466547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2970416,0.0005087384,0.7017083,0.000005831424,0.00007378541,0.0002504722,0.000003674738,0.0003391158,0.00006851897],"genre_scores_gemma":[0.990716,0.00001039531,0.008893464,0.000003395734,0.0000138471,0.0002663788,0.000006333893,0.0000680694,0.00002214458],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6936744,"threshold_uncertainty_score":0.9712394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01375025019770159,"score_gpt":0.2166366450706644,"score_spread":0.2028863948729628,"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."}}