{"id":"W2894895528","doi":"10.1002/cjce.23354","title":"Application of nuclear magnetic resonance permeability models in tight reservoirs","year":2018,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Maersk Oil; Canadian Natural Resources Limited; University of Calgary","keywords":"Permeability (electromagnetism); Tight gas; Materials science; Geology; Chemistry; Petroleum engineering; Hydraulic fracturing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0008768903,0.000871854,0.0009649037,0.0008213139,0.0004205301,0.000879885,0.001137441,0.001045202,0.0006848109],"category_scores_gemma":[0.003264287,0.0004341193,0.0006512859,0.0007604561,0.0009263257,0.002248621,0.001353264,0.0007939889,0.0002175201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001090703,"about_ca_system_score_gemma":0.0008996345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01066201,"about_ca_topic_score_gemma":0.005090413,"domain_scores_codex":[0.9994226,0.0001581143,0.00002925024,0.0001699271,0.000136212,0.00008391992],"domain_scores_gemma":[0.9988816,0.0005134461,0.000229952,0.0001221933,0.0001981854,0.00005466105],"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":[0.00007568101,0.00004416805,0.001327915,0.00004523268,0.00002347451,0.00007859455,0.00005070054,0.9755131,0.01077181,0.004681598,0.000226568,0.007161085],"study_design_scores_gemma":[0.000002784378,0.00002608587,0.0003049601,0.000004226609,0.000005326679,0.00001339497,0.00001229989,0.9949884,0.002294014,0.002133673,0.0002036329,0.00001119186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.299865,0.0008242851,0.6937653,0.0002980606,0.00004592204,0.00008683073,0.0003224415,0.0006014258,0.004190642],"genre_scores_gemma":[0.9755608,0.0003549122,0.0217359,0.00005250302,0.00001357532,0.00009392115,0.0002070867,0.00005934989,0.001921974],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01066201,"threshold_uncertainty_score":0.02119994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006023325101706889,"score_gpt":0.2275163832144514,"score_spread":0.2214930581127446,"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."}}