{"id":"W2728519623","doi":"","title":"Estimating pore fluid saturation in an oil sands reservoir using ensemble tree machine learning algorithms","year":2017,"lang":"en","type":"article","venue":"Saint Mary's University Institutional Repository (Saint Mary's University)","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"HEC Montréal","keywords":"Oil sands; Saturation (graph theory); Petroleum engineering; Geology; Algorithm; Computer science; Mathematics; Materials science; Asphalt","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.000517028,0.0004247339,0.0004360459,0.001006506,0.002198249,0.0002239844,0.0008502534,0.0003267471,0.00002427497],"category_scores_gemma":[0.0001821225,0.0005479532,0.0001897033,0.0005138778,0.0002695274,0.002152467,0.0003357603,0.0008031256,0.000006411691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003131873,"about_ca_system_score_gemma":0.0002504002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001923669,"about_ca_topic_score_gemma":0.000331345,"domain_scores_codex":[0.9977161,0.0003136883,0.0003491971,0.0005922044,0.0005000504,0.0005287057],"domain_scores_gemma":[0.9983998,0.0001395219,0.0001983674,0.0007183849,0.0002294274,0.0003144923],"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":[0.0001925305,0.00006760192,0.008764598,0.0001073472,0.0000725026,0.002017545,0.0002193278,0.9748027,0.005807054,0.003543665,0.00001938511,0.004385753],"study_design_scores_gemma":[0.001646095,0.00008996375,0.008984786,0.0002161467,0.00006290204,0.00009983339,0.0002666054,0.9713186,0.0006300412,0.00005974813,0.01602748,0.0005977891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8905696,0.00007679092,0.08602307,0.00008073716,0.0009283528,0.0001543391,0.00002337143,0.000450649,0.02169313],"genre_scores_gemma":[0.9404082,0.00006392479,0.05516802,0.00000787608,0.0002683544,3.956449e-7,0.0001888136,0.00004115585,0.003853279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04983862,"threshold_uncertainty_score":0.9996972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02122984230273042,"score_gpt":0.2376433521895072,"score_spread":0.2164135098867767,"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."}}