{"id":"W7081924314","doi":"10.1016/j.geoen.2025.214212","title":"A hybrid physics augmented predictive model for friction pressure loss in hydraulic fracturing process based on experimental and field data","year":2025,"lang":"en","type":"article","venue":"Geoenergy Science and Engineering","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nexen (Canada)","funders":"Instituto Politécnico de Bragança","keywords":"Wellhead; Hydraulic fracturing; Perforation; Flow (mathematics); Casing; Geothermal gradient; Fluid dynamics; Fracturing fluid; Borehole; Lead (geology)","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":[0.0002767602,0.0005241128,0.0007982993,0.0004918168,0.0004110289,0.0008355483,0.000962086,0.0009599448,0.001019413],"category_scores_gemma":[0.0006434752,0.0004989697,0.0005563076,0.0005330439,0.0004035696,0.0008720543,0.0004271171,0.0006381369,0.0001800859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005234206,"about_ca_system_score_gemma":0.0008702186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02970975,"about_ca_topic_score_gemma":0.01855651,"domain_scores_codex":[0.9999019,0.00001257184,0.000008111931,0.00003379333,0.0000287687,0.00001484617],"domain_scores_gemma":[0.9997457,0.0001204106,0.00003578354,0.00002102988,0.00006528047,0.0000118775],"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":[0.00003025645,0.00002895885,0.0004788335,0.00002450231,0.00001385066,0.0000269817,0.00001240768,0.9925282,0.0007907722,0.0002452534,0.00009626546,0.005723611],"study_design_scores_gemma":[0.000001868728,0.00000421116,0.0001358997,7.005619e-7,0.000002217921,0.000001578501,0.000001120422,0.9996777,0.00009192086,0.00005922339,0.00002193982,0.000001513412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4701547,0.0006277771,0.520164,0.000281426,0.0001360096,0.0000921439,0.0005562513,0.001545736,0.006441893],"genre_scores_gemma":[0.9947249,0.00007832891,0.004131583,0.00001553191,0.000008740984,0.00003774354,0.0001222898,0.00001601187,0.0008648213],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02970975,"threshold_uncertainty_score":0.05907363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01083364020289616,"score_gpt":0.2334552772529687,"score_spread":0.2226216370500725,"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."}}