{"id":"W3096712958","doi":"10.1080/19401493.2020.1838612","title":"Fluid temperature predictions of geothermal borefields using load estimations via state observers","year":2020,"lang":"en","type":"article","venue":"Journal of Building Performance Simulation","topic":"Geothermal Energy Systems and Applications","field":"Energy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Horizon 2020 Framework Programme","keywords":"Kalman filter; Geothermal gradient; Superposition principle; Estimator; Cooling load; Mathematics; Function (biology); Applied mathematics; Control theory (sociology); Computer science; Mathematical optimization; Engineering; Statistics; Geology; Mathematical analysis","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002039957,0.0001321108,0.000242258,0.0001002822,0.0001706425,0.00002989915,0.0001574907,0.0000968235,0.00006380666],"category_scores_gemma":[0.00005679972,0.0001188291,0.0001221997,0.0003825518,0.00003546193,0.000580418,0.0000214359,0.0002174397,0.000002841766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009519161,"about_ca_system_score_gemma":0.0001261666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001657356,"about_ca_topic_score_gemma":0.000008850011,"domain_scores_codex":[0.9986394,0.00003540087,0.0006951442,0.000115278,0.0003570381,0.0001577177],"domain_scores_gemma":[0.9986334,0.00005514599,0.0006049959,0.0001408265,0.000460481,0.0001051627],"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":[0.0000476308,0.00002668803,0.001653227,0.00005523371,0.00004690983,7.776722e-7,0.0004881195,0.8979532,0.09777964,0.0001780503,0.00001501861,0.001755528],"study_design_scores_gemma":[0.0005042561,0.0001312739,0.007526237,0.0001278554,0.00005134589,0.00001434149,0.00005008234,0.9798418,0.009575188,0.00004172998,0.00202521,0.0001106216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9474409,0.0001267157,0.0517556,0.000238834,0.0001646656,0.00008587418,0.000008042452,0.0000279939,0.0001513517],"genre_scores_gemma":[0.995093,0.00002965236,0.004415605,0.00008645601,0.0003136068,0.000002271231,0.000004179994,0.00002276795,0.00003243667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08820445,"threshold_uncertainty_score":0.4845708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02605690522452971,"score_gpt":0.2644020570706469,"score_spread":0.2383451518461172,"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."}}