{"id":"W2000994408","doi":"10.2118/165480-ms","title":"A New Method for Predicting Friction Losses and Solids Deposition during the Water-Assisted Pipeline Transport of Heavy Oils and Co-Produced Sand","year":2013,"lang":"en","type":"article","venue":"SPE Heavy Oil Conference-Canada","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Saskatchewan Research Council (Canada)","funders":"","keywords":"Pipeline transport; Asphalt; Petroleum engineering; Pressure drop; Fouling; Environmental science; Flow (mathematics); Volumetric flow rate; Geotechnical engineering; Deposition (geology); Materials science; Viscosity; Geology; Environmental engineering; Composite material; Mechanics; Sediment; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004145128,0.0007146898,0.0005597813,0.001049312,0.0003378457,0.0005302451,0.0008968607,0.0007404414,0.001329844],"category_scores_gemma":[0.001089303,0.0004701483,0.0005914454,0.0004732212,0.0002784374,0.0007698309,0.0003573464,0.0005225886,0.0004791567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006922131,"about_ca_system_score_gemma":0.000863623,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009889591,"about_ca_topic_score_gemma":0.007778243,"domain_scores_codex":[0.9997841,0.00001805236,0.00001358377,0.00005000786,0.0001173485,0.00001688302],"domain_scores_gemma":[0.9995242,0.0001871564,0.00006991884,0.00005600751,0.0001394783,0.00002310803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003259536,0.0002158588,0.0104821,0.0002183799,0.00009411156,0.0001553857,0.000150325,0.6390569,0.1582147,0.001592336,0.000685168,0.1888088],"study_design_scores_gemma":[0.00000634969,0.00004479491,0.0006242251,0.000002444501,0.000005930494,0.00001988204,0.000006855079,0.9870548,0.01181097,0.0000723722,0.0003428007,0.000008532096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08541301,0.0001015446,0.9108066,0.00002764762,0.00003071265,0.00009928548,0.0001850711,0.002185056,0.001151052],"genre_scores_gemma":[0.7070021,0.0001674091,0.2888784,0.00001848791,0.00001165439,0.0002193554,0.0002573226,0.0001378269,0.003307429],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9901104,"threshold_uncertainty_score":0.01966405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01486596210226226,"score_gpt":0.2460887159430812,"score_spread":0.2312227538408189,"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."}}