{"id":"W1989015093","doi":"10.2118/63257-ms","title":"Combining NMR and Conventional Logs to Determine Fluid Volumes and Oil Viscosity in Heavy-Oil Reservoirs","year":2000,"lang":"en","type":"article","venue":"SPE Annual Technical Conference and Exhibition","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Petrophysics; Viscosity; Capillary action; Permeability (electromagnetism); Bound water; Porosity; Porous medium; Viscous liquid; Chemistry; Analytical Chemistry (journal); Materials science; Thermodynamics; Chromatography; Physics; Molecule; Organic chemistry; Composite material","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001230156,0.0001234185,0.0001749304,0.00005065846,0.0001481194,0.00007504097,0.00006238743,0.00005615209,0.0003470071],"category_scores_gemma":[0.000005146715,0.0001248332,0.00002414429,0.0001149788,0.000143329,0.0002127597,0.00006685877,0.0001659198,0.00001674228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001110207,"about_ca_system_score_gemma":0.00002345519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003143422,"about_ca_topic_score_gemma":0.0001206364,"domain_scores_codex":[0.9991719,0.00002610268,0.000202417,0.0003090751,0.00009210877,0.0001984095],"domain_scores_gemma":[0.9996584,0.00003629778,0.00002961721,0.0001153154,0.00004051046,0.0001198243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006167618,0.0008922765,0.06158298,0.0001304899,0.00004007394,0.00001360977,0.001088217,0.0000233172,0.07371968,0.3050474,0.004489463,0.5523557],"study_design_scores_gemma":[0.0107574,0.00317237,0.4839016,0.002302374,0.0002103766,0.0001121653,0.004570793,0.008499085,0.05308872,0.3680633,0.0617937,0.003528154],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888539,0.00005601459,0.0006717938,0.001831355,0.000008127854,0.00007262307,0.00008489074,0.00003156627,0.008389775],"genre_scores_gemma":[0.9982957,0.0001135705,0.0006444788,0.0001343819,0.0000591574,0.00004810559,0.0000599228,0.000006636752,0.000638037],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5488276,"threshold_uncertainty_score":0.509055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01711853704654995,"score_gpt":0.302977745379015,"score_spread":0.285859208332465,"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."}}