{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002978388,0.0009840521,0.000465131,0.002821476,0.0005043081,0.001579353,0.0009879147,0.0007884334,0.0024323],"category_scores_gemma":[0.01362764,0.0004723154,0.0007246648,0.001785504,0.0005657481,0.002197984,0.001245324,0.0007537919,0.0002691792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004266544,"about_ca_system_score_gemma":0.003192589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02050325,"about_ca_topic_score_gemma":0.03405713,"domain_scores_codex":[0.9971064,0.0009084995,0.0001514565,0.0001655271,0.001359476,0.0003087196],"domain_scores_gemma":[0.993765,0.003506931,0.0009858544,0.0003677314,0.001232152,0.0001422451],"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":[0.0006453985,0.000303785,0.089026,0.0003115104,0.0002466157,0.0003913302,0.0002262437,0.679517,0.006136956,0.0118423,0.001117385,0.2102355],"study_design_scores_gemma":[0.00005883558,0.001987899,0.1452913,0.0001839751,0.0003877481,0.0004625785,0.001733374,0.8249052,0.008944637,0.01041816,0.005451492,0.0001749858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8690062,0.0008924385,0.1076412,0.0006159141,0.00004605372,0.0008654477,0.001149244,0.0002795561,0.01950403],"genre_scores_gemma":[0.9579931,0.0003662483,0.03955229,0.00002805281,0.000008116516,0.0001642802,0.0004329583,0.00002225437,0.00143278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02050325,"threshold_uncertainty_score":0.04076785,"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."}}