{"id":"W2893203167","doi":"10.2118/191426-ms","title":"Implementation of a Fully Automated Real-Time Torque and Drag Model for Improving Drilling Performance: Case Study","year":2018,"lang":"en","type":"article","venue":"SPE Annual Technical Conference and Exhibition","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Apache (Canada)","funders":"","keywords":"Merge (version control); Casing; Torque; Computer science; Drag; Real-time computing; Drilling; Calibration; Simulation; 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":[0.00135667,0.0008591404,0.0004869034,0.000509233,0.0004657331,0.0009096646,0.002016908,0.001163209,0.003150844],"category_scores_gemma":[0.003096241,0.0004622917,0.0004323769,0.0003938299,0.0005682029,0.001077439,0.0008109149,0.0006428292,0.0009426923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006719147,"about_ca_system_score_gemma":0.001215355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006688399,"about_ca_topic_score_gemma":0.006630269,"domain_scores_codex":[0.9991353,0.0002194427,0.00007655128,0.0001259297,0.0003204482,0.00012233],"domain_scores_gemma":[0.9974994,0.0007786106,0.0001426235,0.000608396,0.0007338776,0.0002370492],"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":[0.001571958,0.002824795,0.02228545,0.001101307,0.0001193695,0.002950025,0.002318882,0.4967503,0.144223,0.002675207,0.00850817,0.3146716],"study_design_scores_gemma":[0.0001611619,0.001266808,0.004983421,0.00004382292,0.00004804806,0.0002796378,0.0004080015,0.9020758,0.08069997,0.0004143312,0.009532503,0.00008656202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7290747,0.0001382517,0.2445084,0.0004153323,0.00009247568,0.0007818737,0.0005343262,0.01807381,0.006380868],"genre_scores_gemma":[0.8867519,0.00004303578,0.1097007,0.00003547367,0.000005304257,0.0001428629,0.0002725273,0.0003078121,0.00274038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006688399,"threshold_uncertainty_score":0.01329893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.014998416135211,"score_gpt":0.2743929601325754,"score_spread":0.2593945439973644,"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."}}