{"id":"W4407252581","doi":"10.3390/cleantechnol7010014","title":"A Numerical Investigation of the Potential of an Enhanced Geothermal System (EGS) for Power Generation at Mount Meager, BC, Canada","year":2025,"lang":"en","type":"article","venue":"Clean Technologies","topic":"Geothermal Energy Systems and Applications","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; Natural Resources Canada; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Geothermal gradient; Multiphysics; Petroleum engineering; Geothermal energy; Environmental science; Thermal energy; Extraction (chemistry); Geology; Engineering; Geophysics; Finite element method; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001363276,0.0003910851,0.0002718507,0.0003242142,0.000891021,0.00091591,0.0006080061,0.0006533748,0.002797474],"category_scores_gemma":[0.0005232355,0.0002187162,0.0003112072,0.000546689,0.0006369468,0.0003585638,0.0003532874,0.0003792799,0.0001595479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005374857,"about_ca_system_score_gemma":0.004927516,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6457269,"about_ca_topic_score_gemma":0.7211052,"domain_scores_codex":[0.9999037,0.000008755075,0.000002187093,0.00001551959,0.00002473882,0.00004507438],"domain_scores_gemma":[0.9998682,0.00004880841,0.00001270914,0.000007861878,0.00003831941,0.00002412496],"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":[0.0001259887,0.00004586776,0.009241214,0.00006765273,0.00001746493,0.0002873888,0.00005312808,0.977356,0.005615633,0.001347212,0.001149117,0.004693415],"study_design_scores_gemma":[0.00004726596,0.00007716924,0.008146313,0.0000117156,0.00002245825,0.00003879536,0.0002761371,0.9868723,0.002683731,0.0003069072,0.001499884,0.00001737506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707106,0.0001314422,0.003340154,0.0003467225,0.00001812619,0.00005251082,0.00102923,0.0001095824,0.02426163],"genre_scores_gemma":[0.9963826,0.00005101185,0.001349467,0.00001534091,0.000001263476,0.00001219006,0.0001466536,0.000009077768,0.002032344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3542731,"threshold_uncertainty_score":0.7127191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007768796040224467,"score_gpt":0.2053323849884621,"score_spread":0.1975635889482376,"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."}}