{"id":"W2000584499","doi":"10.2118/143731-ms","title":"Advancements in Screen Testing, Interpretation and Modeling for Standalone Screen Applications","year":2011,"lang":"en","type":"article","venue":"SPE European Formation Damage Conference","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"ConocoPhillips (Canada)","funders":"ConocoPhillips","keywords":"Slurry; Ranking (information retrieval); Computer science; Monte Carlo method; Simulation; Engineering; Artificial intelligence; Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002016003,0.0001017722,0.0001028574,0.0001393404,0.00006056522,0.00004732035,0.0001313736,0.00002029372,0.00002323642],"category_scores_gemma":[0.00004094159,0.0001017356,0.00001908251,0.0001407083,0.0000194579,0.0004631105,0.00003529211,0.00009085898,0.00002326091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002563782,"about_ca_system_score_gemma":0.000006438525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003690117,"about_ca_topic_score_gemma":0.00007784421,"domain_scores_codex":[0.9993601,0.00002993032,0.0002677932,0.0001227248,0.00007874731,0.0001407056],"domain_scores_gemma":[0.9996321,0.00001960883,0.000047251,0.0001568518,0.00009274004,0.00005144672],"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":[0.00005956566,0.00005670217,0.00147932,0.0003827214,0.000061987,0.000004649014,0.006123162,0.7258757,0.001393375,0.0006738777,0.0001169358,0.263772],"study_design_scores_gemma":[0.0002977997,0.00002404831,0.001229947,0.00008208105,0.00001310462,8.928968e-7,0.0002513317,0.9968021,0.000311929,0.0003663708,0.0004975726,0.0001228389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03936528,0.00005932911,0.9246437,0.00001126329,0.00001593709,0.0002523648,0.00002452592,0.0001164006,0.03551123],"genre_scores_gemma":[0.9821562,0.00006870391,0.01754759,0.00001716696,0.00002093807,0.00002366005,0.00008894047,0.00001858349,0.00005819204],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9427909,"threshold_uncertainty_score":0.4148658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05567540068759834,"score_gpt":0.251213006491998,"score_spread":0.1955376058043997,"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."}}