{"id":"W4412454817","doi":"10.1144/petgeo2023-126","title":"Evaluation of petrophysical rock typing and determination of pore size distribution in a carbonate reservoir using nuclear magnetic resonance","year":2025,"lang":"en","type":"article","venue":"Petroleum Geoscience","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Petrophysics; Igneous petrology; Geology; Carbonate; Engineering geology; Hydrogeology; Carbonate rock; Mineralogy; Petrology; Geochemistry; Geotechnical engineering; Seismology; Porosity; Volcanism; Sedimentary rock; Materials science","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":[0.0003896954,0.00006574235,0.0001196134,0.00004444838,0.00007556386,0.00001390068,0.0001130456,0.00001868193,0.00001422678],"category_scores_gemma":[0.00005872901,0.00006915785,0.00002518076,0.0004191873,0.00008421652,0.0001123396,0.00005618302,0.0000734334,3.674278e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006442898,"about_ca_system_score_gemma":0.0001072811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000401773,"about_ca_topic_score_gemma":0.00001410806,"domain_scores_codex":[0.9991866,0.00005861027,0.0001995759,0.0001971748,0.0002294399,0.0001286045],"domain_scores_gemma":[0.9995468,0.00005442031,0.0001041066,0.0001451438,0.0001333766,0.0000162038],"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":[0.000115723,0.0007700683,0.1265792,0.0001356082,0.00001217974,8.84379e-7,0.0007824304,0.006760779,0.5480837,0.2017419,0.0000160924,0.1150014],"study_design_scores_gemma":[0.0003783082,0.00004096742,0.2013284,0.0000981108,0.00003611164,2.618975e-7,0.0001687826,0.7806945,0.004084705,0.01302723,0.00007489941,0.00006775597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991256,0.0001588293,0.007569894,0.00007123698,0.00002431574,0.0001086329,0.00003060737,0.000004258261,0.0007762476],"genre_scores_gemma":[0.9990969,0.000004033335,0.0008193153,0.000003681504,0.00001367449,0.00001351545,0.00000552733,0.000002928087,0.00004037192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7739337,"threshold_uncertainty_score":0.2820176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01262146362265483,"score_gpt":0.3208596948512335,"score_spread":0.3082382312285787,"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."}}