{"id":"W4301718319","doi":"10.1190/int-2021-0239.1","title":"Applicability of decision tree-based machine learning models in the prediction of core-calibrated shale facies from wireline logs in the late Devonian Duvernay Formation, Alberta, Canada","year":2022,"lang":"en","type":"article","venue":"Interpretation","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Geological Society of America","keywords":"Wireline; Facies; Geology; Decision tree; Sedimentary depositional environment; Petrology; Well logging; Machine learning; Devonian; Artificial intelligence; Data mining; Structural basin; Paleontology; Computer science; Petroleum engineering","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":[0.003031405,0.001052767,0.0005344679,0.001616328,0.0005283716,0.001198504,0.001057834,0.0007427761,0.0005642666],"category_scores_gemma":[0.005008378,0.000295908,0.0007706698,0.0007998717,0.0003565365,0.0004428652,0.0004749987,0.0007104256,0.0002528327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005158588,"about_ca_system_score_gemma":0.002803627,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.481387,"about_ca_topic_score_gemma":0.3614668,"domain_scores_codex":[0.9994212,0.0002327458,0.0000446403,0.0001378442,0.00008942645,0.00007399297],"domain_scores_gemma":[0.9960859,0.002537644,0.0002044584,0.00007623101,0.0009238285,0.0001719161],"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":[0.0003895143,0.0002634785,0.1081156,0.00003685007,0.0001374021,0.00007370418,0.00009357775,0.8472999,0.0009406857,0.000144777,0.0006619417,0.04184245],"study_design_scores_gemma":[0.000007503832,0.00002374913,0.00847921,0.000006937785,0.00001120373,0.000003235567,0.00003644411,0.9909562,0.0003250047,0.00008350545,0.00005998598,0.000006962482],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9865431,0.0001652196,0.01170501,0.0001725774,0.00001274088,0.00005220048,0.0004332393,0.0002223718,0.0006936435],"genre_scores_gemma":[0.9923486,0.00004509872,0.006346249,0.00002975756,0.000004535187,0.00002752686,0.0007495512,0.000009619761,0.0004390976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.518613,"threshold_uncertainty_score":0.95717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01357526303310262,"score_gpt":0.2024782917973376,"score_spread":0.188903028764235,"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."}}