{"id":"W4255575949","doi":"10.32920/ryerson.14647128.v1","title":"Underground Energy Storage Utilizing Concrete Building Foundation: Experimental and Numerical Approach","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Geothermal Energy Systems and Applications","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; National Research Foundation","keywords":"Borehole; Pile; Thermal energy storage; Foundation (evidence); Laminar flow; Parametric statistics; Thermal; Drilling; Environmental science; Flow (mathematics); Volumetric flow rate; Geotechnical engineering; Mechanics; Nuclear engineering; Mechanical engineering; Engineering; Meteorology; Thermodynamics; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0002434096,0.0002883138,0.0004438123,0.0003689547,0.0002950933,0.0002947227,0.0004366671,0.0004754204,0.001497666],"category_scores_gemma":[0.0003004539,0.0001501362,0.0002742143,0.000572638,0.0005158143,0.0003841732,0.0003312789,0.0003331724,0.0001153829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002537847,"about_ca_system_score_gemma":0.0002505914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001213736,"about_ca_topic_score_gemma":0.001168996,"domain_scores_codex":[0.9999002,0.00001157047,0.000006954827,0.0000164558,0.00004043376,0.00002444164],"domain_scores_gemma":[0.9997601,0.0001039792,0.00004236509,0.00003949067,0.00003689701,0.00001719717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009985063,0.001484658,0.006474596,0.00075975,0.00003165248,0.0006575459,0.0002638446,0.2654684,0.7018527,0.002523747,0.0004058675,0.0190788],"study_design_scores_gemma":[0.0001480544,0.002894163,0.007825303,0.00002568127,0.00004470312,0.000185237,0.0003186698,0.5484125,0.4381502,0.0007238988,0.001208601,0.00006290206],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995743,0.00006253959,0.002619594,0.00001583015,0.000007309307,0.00003360268,0.0001880156,0.00005052785,0.001279537],"genre_scores_gemma":[0.9973093,0.00008099023,0.002202927,0.000001493391,0.000001586267,0.00002732181,0.00004898529,0.000002790495,0.0003247098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001497666,"threshold_uncertainty_score":0.005010188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0324438097036239,"score_gpt":0.2725647702740628,"score_spread":0.2401209605704389,"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."}}