{"id":"W4394690201","doi":"10.3390/en17081807","title":"Canada’s Geothermal Energy Update in 2023","year":2024,"lang":"en","type":"article","venue":"Energies","topic":"CO2 Sequestration and Geologic Interactions","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Cenovus Energy (Canada); Geological Survey of Canada; University of Waterloo; University of Alberta; Natural Resources Canada; Alberta Energy","funders":"","keywords":"Geothermal gradient; Geothermal energy; Environmental science; Natural resource economics; Environmental protection; Geology; Economics; Geophysics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00003397784,0.00004794967,0.00003645969,0.0000204399,0.00002825048,0.00002507929,0.00006274956,0.00001820234,0.0122052],"category_scores_gemma":[0.000005544457,0.00004127766,0.00001340437,0.0001040219,0.00002927693,0.0001015228,0.0000365324,0.00004980325,0.00021716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001255964,"about_ca_system_score_gemma":0.00006901731,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8670967,"about_ca_topic_score_gemma":0.9764591,"domain_scores_codex":[0.9996008,0.00001581995,0.00007545658,0.0001148794,0.00008419748,0.0001088201],"domain_scores_gemma":[0.9998837,0.00002071258,0.000006689574,0.00006629912,0.000001205169,0.00002136459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009309737,0.00003143315,0.005066612,0.000005197098,0.00001419473,0.0003816306,0.0002362312,0.2430004,0.004288082,0.08987017,0.6323098,0.02478687],"study_design_scores_gemma":[0.00002306622,0.000004328215,0.01509178,0.000004741735,0.000001067006,0.000007267231,0.00005123448,0.003579716,0.0006907932,0.0006973127,0.9797848,0.00006389506],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5812553,0.0003319656,0.00009281477,0.01097821,0.001209052,0.00003217945,0.00001466667,0.0001023011,0.4059836],"genre_scores_gemma":[0.960793,0.00003294981,0.00004420226,0.0008169335,0.00003428393,0.000007869781,0.000006873561,0.000003281225,0.03826065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3795377,"threshold_uncertainty_score":0.9886978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00556775074071687,"score_gpt":0.2110714769166912,"score_spread":0.2055037261759743,"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."}}