{"id":"W2604577833","doi":"10.3390/en10040447","title":"Hybridising Human Judgment, AHP, Grey Theory, and Fuzzy Expert Systems for Candidate Well Selection in Fractured Reservoirs","year":2017,"lang":"en","type":"article","venue":"Energies","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Southwest Petroleum University; State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation; National Natural Science Foundation of China","keywords":"Analytic hierarchy process; Fuzzy logic; Hydraulic fracturing; Selection (genetic algorithm); Hierarchy; Process (computing); Computer science; Data mining; Engineering; Operations research; Artificial intelligence; Petroleum engineering; Economics","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":[0.005610254,0.0006521175,0.0009129851,0.002313849,0.001082518,0.001392814,0.00076402,0.0009104781,0.001013545],"category_scores_gemma":[0.0107489,0.0004128786,0.0007411096,0.001406587,0.0006988059,0.001350591,0.001225984,0.0007006226,0.0001287535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001425199,"about_ca_system_score_gemma":0.002358568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01126014,"about_ca_topic_score_gemma":0.01580733,"domain_scores_codex":[0.9970744,0.001791579,0.0001597967,0.0002207154,0.000619318,0.0001343257],"domain_scores_gemma":[0.9942854,0.004226385,0.0003262972,0.000181557,0.00080009,0.0001802284],"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":[0.0004708473,0.0004180772,0.006976021,0.0004166592,0.0002338146,0.0003251777,0.002174007,0.7646723,0.008775969,0.0088505,0.0007387609,0.2059478],"study_design_scores_gemma":[0.00002609411,0.0001009226,0.0008950872,0.00002135183,0.00002704182,0.00002148491,0.000267817,0.9921874,0.00141493,0.004668226,0.0003421783,0.00002749577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1969291,0.0002204529,0.7996652,0.0002613919,0.00003861127,0.0002682304,0.00005264515,0.0001919607,0.002372508],"genre_scores_gemma":[0.7590671,0.0001037831,0.240035,0.00005134301,0.00001691668,0.0001401499,0.00004660811,0.00001265816,0.0005264538],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01126014,"threshold_uncertainty_score":0.02967024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1203197338518572,"score_gpt":0.4335901784563225,"score_spread":0.3132704446044653,"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."}}