{"id":"W4317821575","doi":"10.1021/acsomega.2c06918","title":"Prediction of Total Organic Carbon in Organic-Rich Shale Rocks Using Thermal Neutron Parameters","year":2023,"lang":"en","type":"article","venue":"ACS Omega","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Total organic carbon; Oil shale; Source rock; Sampling (signal processing); Petroleum engineering; Mineralogy; Geology; Soil science; Environmental science; Computer science; Chemistry; Environmental chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002960497,0.0005269108,0.0002515739,0.0005943074,0.0002195877,0.0004479066,0.0002903161,0.0004028998,0.0002995115],"category_scores_gemma":[0.0007102597,0.0002075642,0.0003795117,0.0005205324,0.000155066,0.0003752423,0.000179486,0.0002708182,0.0001138294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009664251,"about_ca_system_score_gemma":0.0009761326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07808673,"about_ca_topic_score_gemma":0.1104655,"domain_scores_codex":[0.9999155,0.00000894429,0.000006982873,0.0000291991,0.00002600353,0.00001339427],"domain_scores_gemma":[0.9997436,0.00009139144,0.00004150187,0.00001297384,0.00009429162,0.00001627734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001670101,0.0001846661,0.2128158,0.0001115743,0.00006774184,0.0002055814,0.0001007531,0.7341732,0.01734146,0.0001445745,0.0002859816,0.03440158],"study_design_scores_gemma":[0.000005318334,0.00002848058,0.0454203,0.000005475614,0.00001303618,0.00001356906,0.0000490692,0.9478123,0.006461545,0.00005552581,0.0001246199,0.00001066264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937146,0.00006974406,0.005316392,0.00001641371,0.000003842502,0.00001263507,0.0003010541,0.00006080761,0.0005045418],"genre_scores_gemma":[0.9957766,0.00006851603,0.003368567,0.000004010546,0.000001191039,0.00001227198,0.0004168283,0.000005749318,0.0003462989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07808673,"threshold_uncertainty_score":0.1552644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02083750156122575,"score_gpt":0.216095984623683,"score_spread":0.1952584830624573,"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."}}