{"id":"W2482248492","doi":"10.1139/cgj-2016-0083","title":"Case study of use of falling weight deflectometer to investigate railway infrastructure constructed upon soft subgrades","year":2016,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Falling weight deflectometer; Subgrade; Geotechnical engineering; Deflection (physics); Substructure; Structural engineering; Axle load; Engineering; Levee; Rut; Geology; Axle; Asphalt; Materials science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001751239,0.0002264315,0.000366942,0.0006819508,0.00006743895,0.00004302796,0.0002407387,0.0001964006,0.0000457358],"category_scores_gemma":[0.0003137364,0.0001746136,0.00009166543,0.0004791387,0.00007410524,0.0001620205,0.00002616635,0.0004439206,0.000002566252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002365491,"about_ca_system_score_gemma":0.0001832568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002410975,"about_ca_topic_score_gemma":0.006840501,"domain_scores_codex":[0.9985535,0.00004166707,0.0005746917,0.0001648563,0.0002092782,0.0004559676],"domain_scores_gemma":[0.9983687,0.0001562526,0.000078872,0.0003037503,0.0001494102,0.0009430374],"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":[0.00002029635,0.00002582641,0.01141951,0.00005750692,0.0002779127,0.002712661,0.0005279041,0.9319678,0.03503111,0.0000834482,0.0008657529,0.01701028],"study_design_scores_gemma":[0.01386532,0.004538505,0.0960684,0.003522212,0.001243479,0.122591,0.002744168,0.6970733,0.02802058,0.003525714,0.02031952,0.00648774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689977,0.00004589435,0.03025489,0.00005845555,0.0002937494,0.0001758564,0.00007813996,0.00008682175,0.000008520641],"genre_scores_gemma":[0.9955392,0.00002052511,0.004276882,0.00002942139,0.00007017202,0.000004025021,0.000001156983,0.00004867233,0.000009951674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2348945,"threshold_uncertainty_score":0.7120537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01499315907072911,"score_gpt":0.2089216919809283,"score_spread":0.1939285329101992,"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."}}