{"id":"W2071713133","doi":"10.2118/134528-ms","title":"Getting Smarter and Hotter With ESPs for SAGD","year":2010,"lang":"en","type":"article","venue":"SPE Annual Technical Conference and Exhibition","topic":"Oil and Gas Production Techniques","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"ConocoPhillips (Canada)","funders":"ConocoPhillips","keywords":"Instrumentation (computer programming); Reliability (semiconductor); Test (biology); Fluid dynamics; Computer science; Flow (mathematics); Environmental science; Simulation; Petroleum engineering; Nuclear engineering; Mechanical engineering; Engineering; Geology; Operating system; Physics; Mechanics","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":[0.001027686,0.0003809725,0.0004297448,0.000505299,0.0005688163,0.000533643,0.0006184375,0.0005327312,0.006885688],"category_scores_gemma":[0.002194064,0.0002116951,0.0003588382,0.0003372689,0.0004324997,0.001329096,0.0007286907,0.0005063426,0.001427391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003467018,"about_ca_system_score_gemma":0.0003349118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001069479,"about_ca_topic_score_gemma":0.002480251,"domain_scores_codex":[0.9991474,0.000138482,0.0000540978,0.0001001439,0.0004613709,0.00009849372],"domain_scores_gemma":[0.9988036,0.0002116519,0.00009842979,0.0002178593,0.0005837531,0.00008462922],"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":[0.001315625,0.0005636669,0.04033917,0.0004421109,0.00006842485,0.001066647,0.001260023,0.005414018,0.6854674,0.000526857,0.00547039,0.2580656],"study_design_scores_gemma":[0.0002054908,0.007560233,0.1124302,0.0000867526,0.0001201126,0.001216261,0.003211218,0.01283669,0.8273596,0.0009319478,0.03390139,0.0001401805],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786436,0.0001351145,0.0143026,0.0002522928,0.00009749944,0.0001237546,0.0002254821,0.001139546,0.005080058],"genre_scores_gemma":[0.978215,0.00007210888,0.01634069,0.0001743268,0.0000136006,0.00003369637,0.000319673,0.0001713085,0.004659646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006885688,"threshold_uncertainty_score":0.02303487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008289444863630995,"score_gpt":0.2217671083213329,"score_spread":0.2134776634577019,"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."}}