{"id":"W2128383083","doi":"10.1061/9780784413616.216","title":"Estimating Potential Cost Savings from Implementing an Innovative TBM Guidance Automation System","year":2014,"lang":"en","type":"article","venue":"Computing in Civil and Building Engineering (2014)","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Automation; Context (archaeology); Reliability (semiconductor); Cost estimate; Identification (biology); Crew; Computer science; Reliability engineering; Productivity; Risk analysis (engineering); Field (mathematics); Engineering; Systems engineering; Business; Aeronautics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009456069,0.0003101915,0.0003481203,0.0002463062,0.0002076462,0.0001597689,0.0002178569,0.0001299725,0.000003536923],"category_scores_gemma":[0.0001318763,0.000343005,0.00003484042,0.0003017986,0.00001000303,0.0002208685,0.0001434203,0.0003568132,0.000004824213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001502582,"about_ca_system_score_gemma":0.00001225774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000098261,"about_ca_topic_score_gemma":0.00001412315,"domain_scores_codex":[0.998232,0.00004064252,0.0005654909,0.000406456,0.0001954415,0.0005599899],"domain_scores_gemma":[0.9992894,0.0001640953,0.0001180685,0.00024878,0.00008139864,0.00009828035],"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":[0.000001527756,0.000007547304,0.0005477312,0.0002890995,0.00001943763,0.000004673778,0.0005608061,0.9610531,0.0254643,0.0005467825,0.00007760664,0.01142733],"study_design_scores_gemma":[0.000390656,0.00002052547,0.002752113,0.001031871,0.00001300171,0.00001858912,0.00007033176,0.993012,0.001943294,0.00006004659,0.0003030923,0.0003845111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4841338,0.0001138939,0.5140535,0.000006085683,0.0007278122,0.00008272163,0.000004475526,0.0008389013,0.0000388336],"genre_scores_gemma":[0.892822,0.000003903629,0.1064545,0.00001293585,0.0006030342,0.000008653381,0.00002291684,0.00007018315,0.000001815375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4086882,"threshold_uncertainty_score":0.9999022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005304499520937679,"score_gpt":0.2132126898677817,"score_spread":0.2079081903468441,"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."}}