{"id":"W4311773340","doi":"10.1007/s10064-022-03008-z","title":"Determination of geotechnical parameters for underground trenchless construction design","year":2022,"lang":"en","type":"article","venue":"Bulletin of Engineering Geology and the Environment","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Emissions Reduction Alberta; University of Alberta","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Geotechnical engineering; Trenchless technology; Standard penetration test; Geotechnical investigation; Modulus; Engineering; Shear strength (soil); Geology; Soil water; Mathematics; Soil science; Pipeline transport","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003364458,0.0001196308,0.0002234534,0.00006256945,0.00006523611,0.000002933985,0.0001199227,0.00007060183,0.00004839916],"category_scores_gemma":[0.00004279936,0.0001053396,0.00006730581,0.00003722582,0.000196095,0.000007518471,0.00005777531,0.0001743671,3.086058e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003237455,"about_ca_system_score_gemma":0.000003115928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009325905,"about_ca_topic_score_gemma":7.924289e-8,"domain_scores_codex":[0.9993505,0.00003820821,0.0002470945,0.0001192279,0.00009840597,0.0001465881],"domain_scores_gemma":[0.9992487,0.0005186463,0.00005132229,0.0001528893,0.000004620055,0.00002381025],"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":[0.00004827375,0.00001081245,0.000004187734,0.00005378497,0.00003703163,4.250792e-7,0.00003121275,0.9844639,0.0007412112,0.01272281,0.00005272182,0.001833595],"study_design_scores_gemma":[0.002954174,0.0004513575,0.001007518,0.0000199383,0.0001370119,0.0001145458,0.0001278898,0.9591469,0.004202389,0.0101242,0.02133863,0.0003755084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0770104,0.000721624,0.9213327,0.0002728997,0.0002123517,0.0003273895,0.000008154725,0.00007397537,0.0000405713],"genre_scores_gemma":[0.9653448,0.0001253949,0.03431421,0.000008860595,0.000009389382,0.0001527318,0.000004875727,0.0000158465,0.00002381778],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8883345,"threshold_uncertainty_score":0.4295623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006657275053084882,"score_gpt":0.1676431836251232,"score_spread":0.1609859085720383,"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."}}