{"id":"W4255328108","doi":"10.3846/13928619.2007.9637813","title":"THE USE OF EXPLORATORY TUNNELS AS A TOOL FOR SCHEDULING AND COST ESTIMATION","year":2007,"lang":"en","type":"article","venue":"Technological and Economic Development of Economy","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Duration (music); Scheduling (production processes); Computer science; Excavation; Monte Carlo method; Estimation; Exploratory research; Project management; Track (disk drive); Operations research; Cost estimate; Engineering; Systems engineering; Operations management; Statistics; Geotechnical 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":[0.002254552,0.0006219794,0.0005268009,0.001987659,0.0003330476,0.0006804029,0.0005967456,0.0004558066,0.001307132],"category_scores_gemma":[0.01010229,0.0005793941,0.0005135674,0.001752138,0.0003063409,0.0009467049,0.0004936586,0.0003632325,0.000224359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005544849,"about_ca_system_score_gemma":0.001218448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00668355,"about_ca_topic_score_gemma":0.009972243,"domain_scores_codex":[0.9984406,0.0008951989,0.00008085631,0.0001557378,0.0003640324,0.00006366696],"domain_scores_gemma":[0.9892111,0.00781048,0.001375257,0.000817339,0.000643488,0.0001423404],"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":[0.000105455,0.0000538036,0.01605045,0.00005570519,0.00004507256,0.00007913981,0.000113049,0.9416103,0.002440884,0.003647855,0.0002864753,0.03551188],"study_design_scores_gemma":[0.000009115626,0.0001821868,0.005938293,0.00001936045,0.00001423141,0.0001118908,0.00006487937,0.9896265,0.001390054,0.001504149,0.001103912,0.00003533868],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2322378,0.0001377932,0.7639471,0.00006567703,0.00001255527,0.0001654929,0.0006982738,0.0005515883,0.002183706],"genre_scores_gemma":[0.829779,0.0001427903,0.1687856,0.000005736798,0.000007254926,0.0001649212,0.0005476702,0.00005534513,0.0005117629],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00668355,"threshold_uncertainty_score":0.01328933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04061395175653917,"score_gpt":0.2246681534651934,"score_spread":0.1840542017086542,"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."}}