{"id":"W2889409659","doi":"10.2118/190945-ms","title":"One Company's Experience using Metal to Metal PCPs as the Primary Artificial Lift Method in a SAGD Operation","year":2018,"lang":"en","type":"article","venue":"","topic":"Oil and Gas Production Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"PetroChina Company Limited","keywords":"Artificial lift; Robustness (evolution); Lift (data mining); Reliability (semiconductor); Computer science; Engineering; Process engineering; Reliability engineering; Petroleum engineering; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000410842,0.0001146134,0.0001685277,0.0001077128,0.00009488234,0.00007402108,0.0001366638,0.00004672608,0.0002208537],"category_scores_gemma":[0.00004034535,0.00009070678,0.00003681555,0.0003028136,0.00004902928,0.000331316,0.00005318326,0.0001146386,0.00007156456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007116367,"about_ca_system_score_gemma":0.00001980017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003290194,"about_ca_topic_score_gemma":0.0001359429,"domain_scores_codex":[0.9991369,0.00006496106,0.0002434884,0.000205266,0.0001649639,0.0001844209],"domain_scores_gemma":[0.999648,0.00002181747,0.00001602662,0.0002230311,0.00004679741,0.00004435237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002918443,0.00006912403,0.00003461173,0.00001325039,0.00003507179,0.000001574446,0.005573499,0.003548221,0.8757427,0.001739935,0.0002060898,0.1130067],"study_design_scores_gemma":[0.00005270212,0.00006477668,0.0006032622,0.000009823953,0.00001341855,0.00001108094,0.0004796044,0.01279264,0.9831704,0.0006216959,0.002020092,0.0001604885],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8630853,0.00005980145,0.130404,0.0005407651,0.0003702903,0.0002914159,0.000001213525,0.0003887543,0.004858419],"genre_scores_gemma":[0.8768677,0.000004119713,0.122269,0.0003695134,0.0003214476,0.00004081257,0.000001998163,0.00001687382,0.0001085573],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1128462,"threshold_uncertainty_score":0.3698915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04781662481775799,"score_gpt":0.3189882866667161,"score_spread":0.2711716618489581,"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."}}