{"id":"W2055344754","doi":"10.1139/t06-074","title":"Probabilistic analysis of drilled shaft service limit state using the \"<i>t</i>–<i>z</i>\" method","year":2006,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Geotechnical Engineering and Analysis","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Limit state design; Serviceability (structure); Structural engineering; Engineering; Monte Carlo method; Probabilistic logic; Limit load; Displacement (psychology); Log-normal distribution; Probabilistic analysis of algorithms; Geotechnical engineering; Mathematics; Finite element method; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001190126,0.0003454967,0.0003085786,0.001479919,0.000230463,0.0004671183,0.0004951351,0.0003050236,0.002658317],"category_scores_gemma":[0.005539699,0.0002414647,0.0005112004,0.0005615553,0.0005764815,0.0007385474,0.0003632185,0.0003340056,0.0002448549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006375302,"about_ca_system_score_gemma":0.0008572878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004326187,"about_ca_topic_score_gemma":0.003402632,"domain_scores_codex":[0.9994829,0.0001197268,0.0000318516,0.00007076303,0.0002542701,0.00004049289],"domain_scores_gemma":[0.9979584,0.00128036,0.0002920151,0.0001382194,0.0002931177,0.00003779825],"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":[0.00008565987,0.0000320632,0.006182466,0.0001142009,0.00003323902,0.0001188293,0.000115226,0.8711196,0.009219022,0.03718216,0.0005666052,0.0752309],"study_design_scores_gemma":[0.000006262166,0.00003416496,0.001247974,0.000007911501,0.000007125293,0.00009214666,0.00001650615,0.9891572,0.002900995,0.005915157,0.0006012195,0.00001325871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02389785,0.00004723963,0.9748781,0.00001490713,0.000002797272,0.00002050731,0.00003776843,0.0001986921,0.0009021118],"genre_scores_gemma":[0.8154439,0.0001876489,0.1826265,0.00001753974,0.000009531272,0.0001233483,0.0002048942,0.00005240415,0.001334166],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004326187,"threshold_uncertainty_score":0.008892953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00991107482274899,"score_gpt":0.2204211727088589,"score_spread":0.2105100978861099,"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."}}