{"id":"W2902048032","doi":"10.2118/192460-ms","title":"Rapid and Comprehensive Artificial Lift Systems Performance Analysis Through Data Analytics, Diagnostics and Solution Evaluation","year":2018,"lang":"en","type":"article","venue":"","topic":"Oil and Gas Production Techniques","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Computer science; Workflow; Benchmarking; Analytics; Asset management; Data analysis; Field (mathematics); Data science; Lift (data mining); Decision support system; Risk analysis (engineering); Data mining; Systems engineering; Engineering; Database","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":[],"consensus_categories":[],"category_scores_codex":[0.0002863558,0.0001011551,0.0001620797,0.0001097192,0.0001046617,0.00006735212,0.00007296063,0.00005597795,0.00002853288],"category_scores_gemma":[0.00005248857,0.00009304827,0.00001294435,0.0002926935,0.00009877258,0.0003592693,0.00006412399,0.0000604101,0.000007506328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002188327,"about_ca_system_score_gemma":0.000007465788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008561892,"about_ca_topic_score_gemma":0.00005570137,"domain_scores_codex":[0.999253,0.00003096834,0.0001991807,0.0002346947,0.0001625452,0.0001195854],"domain_scores_gemma":[0.9993299,0.00004026648,0.00003290497,0.0003583174,0.0002065069,0.00003214403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006199805,0.0001300128,0.02601111,0.0007976567,0.002814516,0.000002262672,0.002264356,0.02070353,0.003593281,0.001788201,0.06041228,0.8814208],"study_design_scores_gemma":[0.00007411556,0.00006194751,0.009361114,0.00001386114,0.000525061,0.000003515176,0.0001133607,0.9795966,0.005259521,0.0001400195,0.00471342,0.0001374648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9363414,0.005005164,0.05508777,0.0002336194,0.0006976552,0.0004100133,0.0000524911,0.0005414026,0.001630496],"genre_scores_gemma":[0.9932508,0.004115013,0.00213252,0.00002097516,0.0003263628,0.000007987486,0.0001096159,0.000008930444,0.00002781614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9588931,"threshold_uncertainty_score":0.3794398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1083934399709837,"score_gpt":0.3002066591211329,"score_spread":0.1918132191501492,"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."}}