{"id":"W2315711638","doi":"10.2118/174837-ms","title":"Sand Control Screen Erosion: Prediction and Avoidance","year":2015,"lang":"en","type":"article","venue":"SPE Annual Technical Conference and Exhibition","topic":"Erosion and Abrasive Machining","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"ConocoPhillips (Canada)","funders":"Southwest Research Institute","keywords":"Erosion; Subsea; Computational fluid dynamics; Completion (oil and gas wells); Flow (mathematics); Geotechnical engineering; Petroleum engineering; Current (fluid); Work (physics); Geology; Environmental science; Engineering; Mechanics; Mechanical engineering","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":[0.0003928796,0.0004450971,0.0004611027,0.0004044616,0.0001629592,0.0006903911,0.0003864874,0.0004282875,0.0005086142],"category_scores_gemma":[0.001111496,0.0002285951,0.0002515703,0.0002027112,0.0001819881,0.0002866236,0.0002304935,0.0003890672,0.00009184978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004788723,"about_ca_system_score_gemma":0.0005677836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01670639,"about_ca_topic_score_gemma":0.01063802,"domain_scores_codex":[0.9998969,0.00001558181,0.000005883818,0.00003017632,0.00003070319,0.00002073835],"domain_scores_gemma":[0.9994441,0.0002925652,0.00008065049,0.00002979862,0.0001126496,0.00004032792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001770001,0.0001301552,0.02098597,0.00002171745,0.00001329975,0.00006649686,0.00001455998,0.9554141,0.002896037,0.0001895438,0.0001835664,0.01990764],"study_design_scores_gemma":[0.000003782666,0.0000276528,0.001817093,0.000001128687,0.000001775521,0.0000048153,0.0000029453,0.9973963,0.0006858404,0.00002915205,0.00002762217,0.000001826446],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9486864,0.0001033801,0.0492663,0.00005424175,0.000007359954,0.00004632681,0.0001010962,0.0003603189,0.001374672],"genre_scores_gemma":[0.9929608,0.00002830742,0.006472363,0.000003088743,0.000001859138,0.000008263588,0.0000547059,0.00000510287,0.0004655233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01670639,"threshold_uncertainty_score":0.03321826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02325998414633952,"score_gpt":0.2517385014588764,"score_spread":0.2284785173125369,"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."}}