{"id":"W2592319772","doi":"10.1155/2017/9642917","title":"A New Calculation Method of Dynamic Kill Fluid Density Variation during Deep Water Drilling","year":2017,"lang":"en","type":"article","venue":"Mathematical Problems in Engineering","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"National Natural Science Foundation of China","keywords":"Superposition principle; Drilling fluid; Petroleum engineering; Drilling; Process (computing); Multiphase flow; Geology; Mechanics; Computer science; Engineering; Mechanical engineering; Mathematics; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004818572,0.0002713108,0.000436886,0.0002157975,0.00007916147,0.00007690768,0.0002629134,0.0001666591,0.00002520513],"category_scores_gemma":[0.0001493977,0.0002529726,0.00009506812,0.00008945413,0.00001273002,0.0003005298,0.0000815414,0.0002757372,0.00001852068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001443782,"about_ca_system_score_gemma":0.00000626461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002889821,"about_ca_topic_score_gemma":0.000007772932,"domain_scores_codex":[0.9984841,0.00001154685,0.0005986518,0.0002368641,0.0002233759,0.0004454353],"domain_scores_gemma":[0.9992079,0.00007619386,0.00005858561,0.0005128531,0.00003204853,0.0001124734],"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":[0.000002056999,0.00001500907,0.00003109165,0.001070059,0.00003127898,0.000003321454,0.0008381966,0.8113731,0.1848638,0.0004170164,8.583577e-7,0.001354271],"study_design_scores_gemma":[0.0005984324,0.00001135736,0.001058965,0.0004853636,0.0000235178,0.0000159419,0.000005356703,0.9571232,0.0383549,0.002026161,0.00001135751,0.0002854711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1350431,0.00006318012,0.8638737,0.00001308742,0.000252958,0.0002096376,0.00000101341,0.0002937653,0.0002495185],"genre_scores_gemma":[0.8953057,0.00001724243,0.1044777,8.283204e-7,0.00005994586,0.00001654985,0.000004797616,0.0000762006,0.00004096755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7602626,"threshold_uncertainty_score":0.9999923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006413132315487329,"score_gpt":0.2176908200787745,"score_spread":0.2112776877632872,"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."}}