{"id":"W4251678012","doi":"10.2523/75246-ms","title":"Geological Characterization Of Naturally Fractured Reservoirs Using Multiple Point Geostatistics","year":2002,"lang":"en","type":"article","venue":"Proceedings of SPE/DOE Improved Oil Recovery Symposium","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Citation; Computer science; Point (geometry); Geostatistics; Download; Information retrieval; Geology; Data mining; Library science; World Wide Web; Mathematics; Spatial variability; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000332015,0.0003373199,0.000543994,0.0002728619,0.0000577047,0.00006507585,0.0003068705,0.0003155661,0.0001090398],"category_scores_gemma":[0.0005344542,0.0003283122,0.0001511832,0.0004074764,0.00006827281,0.0006484151,0.00007411141,0.0003693785,0.000005266994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001086797,"about_ca_system_score_gemma":0.00001156776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002574642,"about_ca_topic_score_gemma":9.275189e-7,"domain_scores_codex":[0.9980811,0.00001240707,0.0008255424,0.0003234935,0.0003382624,0.0004191942],"domain_scores_gemma":[0.9987159,0.0001906855,0.0003136849,0.0001774524,0.0004691198,0.0001331694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006968195,0.00004920431,0.0008863637,0.0007061645,0.00006657046,0.000001139891,0.0002815876,0.1394439,0.8554244,0.00004585494,0.00007928148,0.002945868],"study_design_scores_gemma":[0.0006755639,0.0001346406,0.001622769,0.0001342061,0.0000399934,0.000008842612,0.00003160436,0.8616961,0.1344763,0.0001204168,0.0007347235,0.0003248524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808732,0.0002078228,0.01591529,0.0001140465,0.0005572792,0.0001878962,0.00008604811,0.000241647,0.001816778],"genre_scores_gemma":[0.9302195,0.0007592863,0.06816693,0.0000215087,0.0001627906,0.00001238624,0.00003371124,0.00007687746,0.0005469576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7222522,"threshold_uncertainty_score":0.9999169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01500186667843738,"score_gpt":0.2225691929130912,"score_spread":0.2075673262346538,"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."}}