{"id":"W4244867768","doi":"10.2523/iptc-17625-ms","title":"Advanced Rock Characterization by Dual Energy CT Imaging: A Novel Method in Complex Reservoir Evaluation","year":2014,"lang":"en","type":"article","venue":"International Petroleum Technology Conference","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Haliburton Forest & Wild Life Reserve","funders":"","keywords":"Petrophysics; Geology; Lithology; Core (optical fiber); Reservoir modeling; Core sample; Characterization (materials science); Consistency (knowledge bases); Well logging; Mineralogy; Porosity; Petrology; Geophysics; Computer science; Petroleum engineering; Materials science; Geometry; Mathematics; Geotechnical engineering","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":[0.0003487827,0.0002027718,0.0002495037,0.0008045206,0.00004536477,0.00006103494,0.0004334831,0.00009678527,0.0002494523],"category_scores_gemma":[0.0001851974,0.0002186378,0.00005221065,0.0004508849,0.00003981938,0.0003250462,0.00008168872,0.000243619,0.00002864627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001918431,"about_ca_system_score_gemma":0.00003506513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003820773,"about_ca_topic_score_gemma":0.00013338,"domain_scores_codex":[0.9984757,0.00007195739,0.0004257693,0.0003513118,0.000430328,0.0002449466],"domain_scores_gemma":[0.9992453,0.00004495273,0.0001083959,0.0002830823,0.0002680209,0.0000502113],"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":[0.00001848043,0.0000974021,0.0019803,0.000008793633,0.00008325573,0.00000382096,0.00004495981,0.149278,0.8051447,0.01112875,0.0003760518,0.0318355],"study_design_scores_gemma":[0.0008912904,0.00001824636,0.001022373,0.00001828426,0.00001432954,0.0000164851,0.00005910703,0.9588386,0.01195551,0.001707963,0.02524936,0.0002084715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1380405,0.0000381064,0.8513861,0.004660767,0.0002449446,0.00007992803,0.00003573671,0.0003972775,0.005116675],"genre_scores_gemma":[0.9966205,0.00005063316,0.001832061,0.0001437404,0.00004576896,0.0001455185,0.0008719885,0.00002653148,0.0002633004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8585799,"threshold_uncertainty_score":0.8915792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01742348094541446,"score_gpt":0.2736801675876304,"score_spread":0.256256686642216,"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."}}