{"id":"W4254139136","doi":"10.2118/166297-ms","title":"Hydrocarbon Saturation From Total Organic Carbon Logs Derived From Inelastic and Capture Nuclear Spectroscopy","year":2013,"lang":"en","type":"article","venue":"SPE Annual Technical Conference and Exhibition","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Suncor Energy Incorporated","keywords":"Saturation (graph theory); Petrophysics; Hydrocarbon; Porosity; Well logging; Water saturation; Total organic carbon; Petroleum engineering; Lithology; Mineralogy; Calibration; Oil sands; Geology; Soil science; Environmental science; Asphalt; Chemistry; Materials science; Environmental chemistry; Geotechnical engineering; Petrology; Composite material","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003829145,0.0002226941,0.0002708452,0.00008523399,0.00006935926,0.0001416318,0.00007448599,0.0002583706,0.0003889177],"category_scores_gemma":[0.00004075557,0.0002014762,0.00004172083,0.0001632373,0.00009247215,0.0003754485,0.00005418626,0.0003222241,0.0000487118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004337647,"about_ca_system_score_gemma":0.00001406682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001166087,"about_ca_topic_score_gemma":0.0004586178,"domain_scores_codex":[0.99898,0.00003540504,0.0002624712,0.0003294621,0.000177152,0.0002155522],"domain_scores_gemma":[0.9995037,0.00004124086,0.00004203951,0.0001824547,0.00007622588,0.0001542903],"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":[0.00001627229,0.00002072565,0.000172292,0.00001178996,0.00003962822,0.000004626567,0.0005120648,0.0001268861,0.9980963,0.0002118286,0.0003105087,0.0004770179],"study_design_scores_gemma":[0.002460269,0.0005702915,0.07064661,0.0003780214,0.000463811,0.00002926453,0.005605092,0.7387223,0.1380418,0.04068195,0.0002986765,0.002101902],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938974,0.000269301,0.002919869,0.0005322364,0.0000776102,0.0001834336,0.00003585432,0.0003426278,0.001741644],"genre_scores_gemma":[0.9986319,0.0004041237,0.0004549446,0.00009548492,0.0001486951,0.00001617579,0.0002043573,0.00002889148,0.0000154297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8600546,"threshold_uncertainty_score":0.8215961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00725199725312373,"score_gpt":0.1969917446861788,"score_spread":0.1897397474330551,"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."}}