{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00101413,0.001215056,0.0009257628,0.001478554,0.0002161325,0.002072227,0.001935779,0.001188242,0.002228057],"category_scores_gemma":[0.002693791,0.0005518103,0.001212091,0.001155742,0.0004801272,0.001517995,0.0007806218,0.0008788129,0.00091325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008791914,"about_ca_system_score_gemma":0.0006591414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006409081,"about_ca_topic_score_gemma":0.004093714,"domain_scores_codex":[0.9989914,0.0001783126,0.000068024,0.0001467667,0.0005701716,0.00004527112],"domain_scores_gemma":[0.9977505,0.0009552691,0.000280039,0.0003288545,0.00063884,0.00004656211],"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":[0.000240426,0.000233,0.01407293,0.001287207,0.0001835984,0.0004719692,0.000306127,0.6365406,0.0699709,0.01103714,0.004579184,0.2610769],"study_design_scores_gemma":[0.00000873834,0.00008871078,0.003034975,0.00005856037,0.00004899197,0.0001259138,0.00004164036,0.9703196,0.01493435,0.002279646,0.009014757,0.00004415456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1047396,0.00408535,0.8737077,0.0005005451,0.0001421532,0.0001794577,0.001214484,0.005489895,0.00994093],"genre_scores_gemma":[0.8156687,0.004785771,0.1725896,0.0001462435,0.0001112927,0.000214739,0.001174665,0.0006260969,0.004682818],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006409081,"threshold_uncertainty_score":0.01274353,"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."}}