{"id":"W2941357531","doi":"10.1139/cgj-2018-0560","title":"Strain-softening model evaluating geobelt–clay interaction validated by laboratory tests of sensor-enabled geobelts","year":2019,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Geotechnical Engineering and Soil Stabilization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geosynthetics; Geotechnical engineering; Softening; Direct shear test; Dilatant; Soil water; Hydrogeology; Displacement (psychology); Shear (geology); Shear stress; Structural engineering; Materials science; Geology; Engineering; Composite material; Soil science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007671269,0.0002664807,0.0003637119,0.0003299369,0.0001089288,0.00008175059,0.0002894985,0.0003712918,0.0001707308],"category_scores_gemma":[0.0003800462,0.0002838591,0.0001148353,0.0004421526,0.00003763483,0.0002898555,0.00002514433,0.001116218,0.00003426044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005688358,"about_ca_system_score_gemma":0.0003285455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006720248,"about_ca_topic_score_gemma":0.0001868946,"domain_scores_codex":[0.998002,0.0000612154,0.0006691976,0.0002460238,0.0003887803,0.0006327669],"domain_scores_gemma":[0.9985262,0.000110767,0.0001266927,0.0003267004,0.0003124356,0.0005972242],"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":[0.000005433012,0.000009971367,0.00004101432,0.00004253558,0.00002846268,0.000007309162,0.00003626022,0.8264781,0.1702497,0.00004461676,0.0007490108,0.002307605],"study_design_scores_gemma":[0.0004675351,0.00009514052,0.000312505,0.0001782339,0.00003151973,0.00006491573,0.00004789839,0.9935707,0.003039444,0.0002075129,0.001658149,0.0003264807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9411137,0.0003244271,0.05628339,0.0001822571,0.0005177332,0.0003273968,0.0001760487,0.0004447043,0.0006304],"genre_scores_gemma":[0.9980751,0.00004067459,0.001523053,0.00007884479,0.000066531,0.000007703605,0.00004385648,0.00007469988,0.00008951891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1672103,"threshold_uncertainty_score":0.9999614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01211088205264298,"score_gpt":0.2350412580932426,"score_spread":0.2229303760405996,"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."}}