{"id":"W2028704904","doi":"10.1061/(asce)0733-9364(2001)127:6(476)","title":"Applications of Horizontal Characterization Techniques in Trenchless Construction","year":2001,"lang":"en","type":"article","venue":"Journal of Construction Engineering and Management","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Western University","funders":"","keywords":"Trenchless technology; Characterization (materials science); Software deployment; Construction engineering; Computer science; Field (mathematics); Horizontal and vertical; Systems engineering; Work (physics); Representation (politics); Engineering; Civil engineering; Pipeline transport; Geology; Software engineering; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001018293,0.000368144,0.0002571734,0.002285388,0.0004363535,0.0008849798,0.0004381097,0.0004487547,0.002615158],"category_scores_gemma":[0.003865699,0.0002578333,0.0002107653,0.002976958,0.0005615405,0.0009113073,0.0008755419,0.0003839133,0.0004475421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005375343,"about_ca_system_score_gemma":0.0009293579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004806442,"about_ca_topic_score_gemma":0.007832646,"domain_scores_codex":[0.998866,0.000449414,0.00005407565,0.0001232198,0.0004228268,0.0000845685],"domain_scores_gemma":[0.9970094,0.001482108,0.0004494368,0.0003953034,0.0006103722,0.0000534079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001246144,0.00008748651,0.03089337,0.0003224377,0.00003292589,0.0003102856,0.001048411,0.08722244,0.02386324,0.02097922,0.001219461,0.833896],"study_design_scores_gemma":[0.00004570881,0.00101479,0.07637417,0.0003817084,0.0001089956,0.00145594,0.005138757,0.7028998,0.1136868,0.06074255,0.03791998,0.000230812],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1251701,0.0005847173,0.8627078,0.0001380081,0.00001649052,0.0002073214,0.0002343571,0.0006919458,0.01024924],"genre_scores_gemma":[0.7304901,0.0005526523,0.2661884,0.00002600428,0.000009435971,0.0001130677,0.0002086986,0.00005544453,0.002356228],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004806442,"threshold_uncertainty_score":0.00955689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00261671785786741,"score_gpt":0.1784036530515172,"score_spread":0.1757869351936498,"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."}}