{"id":"W1989850047","doi":"10.2118/2003-006","title":"Application of Intelligent System (DES PCP) For Monitoring Progressing Cavity Pumps","year":2003,"lang":"en","type":"article","venue":"Canadian International Petroleum Conference","topic":"Oil and Gas Production Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Engineering","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":[0.0001581724,0.00009742598,0.0001120623,0.0001466715,0.00006021834,0.00004594255,0.000166676,0.00005229206,0.00001330468],"category_scores_gemma":[0.00005459713,0.0001097792,0.00004220593,0.00006745039,0.00004610092,0.0001153253,0.000005406951,0.00007542543,0.000005218096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004481488,"about_ca_system_score_gemma":0.00009401185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003467347,"about_ca_topic_score_gemma":0.002294337,"domain_scores_codex":[0.999327,0.00001200891,0.0002262726,0.0001498003,0.000114135,0.0001707538],"domain_scores_gemma":[0.9993943,0.00001890826,0.00005468489,0.0001346979,0.0002831408,0.0001142908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003866294,0.00008009605,0.1116091,0.001682783,0.0003831692,0.000008079118,0.00088517,0.03742979,0.03876736,0.3200703,0.0006452998,0.4884001],"study_design_scores_gemma":[0.0004026286,0.00007568692,0.01519837,0.0005289364,0.00002829648,0.00004279521,0.0008953435,0.07074711,0.8373772,0.005280028,0.06880271,0.000620903],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8470416,0.000488612,0.1218801,0.0001649551,0.002007028,0.0003939721,0.0001378342,0.0004059324,0.02748002],"genre_scores_gemma":[0.9955642,0.00002762808,0.003980117,0.000003413626,0.00009117553,0.0001483392,0.00001494197,0.00001575255,0.0001544774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7986099,"threshold_uncertainty_score":0.5241614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02139049584870946,"score_gpt":0.2505387688324646,"score_spread":0.2291482729837552,"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."}}