{"id":"W4200015295","doi":"10.3390/w13243526","title":"Are Engineered Geothermal Energy Systems a Viable Solution for Arctic Off-Grid Communities? A Techno-Economic Study","year":2021,"lang":"en","type":"article","venue":"Water","topic":"Geothermal Energy Systems and Applications","field":"Energy","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Geothermal energy; Geothermal gradient; Environmental science; Work (physics); Petroleum engineering; Fossil fuel; Thermal energy; Process engineering; Engineering; Geology; Waste management; Mechanical engineering; Geophysics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001685179,0.0002076852,0.0003205715,0.00008004578,0.0002420346,0.0001129408,0.0002213665,0.0001150324,0.000254335],"category_scores_gemma":[0.000004780243,0.0001711621,0.0001063216,0.00006739412,0.00002868979,0.0001068727,0.0000868866,0.00009031846,0.0001157453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001390097,"about_ca_system_score_gemma":0.0000268818,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06473662,"about_ca_topic_score_gemma":0.008694625,"domain_scores_codex":[0.9987842,0.00008692666,0.000366185,0.000248101,0.00009999829,0.0004146183],"domain_scores_gemma":[0.9990146,0.00003951401,0.0001098124,0.0006580857,0.0001128794,0.00006512253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005706965,0.0007573513,0.001764674,0.0002314132,0.000541946,0.00002157552,0.001658269,0.9492601,0.01965993,0.02393018,0.001064587,0.00105296],"study_design_scores_gemma":[0.002174754,0.0001349369,0.001073704,0.0001232283,0.0001115757,0.00007408565,0.007327309,0.297183,0.009793207,0.0003596143,0.6809722,0.00067236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992185,0.0004581061,0.002945547,0.0004328093,0.0008542382,0.0005629645,0.00009846795,0.0003137125,0.002149159],"genre_scores_gemma":[0.9889551,0.000006192255,0.00007207591,0.0001029669,0.0004134686,0.001536095,0.0001823061,0.00006703106,0.008664788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6799077,"threshold_uncertainty_score":0.9414914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01769669113611166,"score_gpt":0.2135949309488661,"score_spread":0.1958982398127544,"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."}}