{"id":"W2982248341","doi":"10.1016/j.est.2019.100992","title":"Evaluating energy and greenhouse gas emission footprints of thermal energy storage systems for concentrated solar power applications","year":2019,"lang":"en","type":"article","venue":"Journal of Energy Storage","topic":"Adsorption and Cooling Systems","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Thermal energy storage; Sensible heat; Environmental science; Greenhouse gas; Energy storage; Solar energy; Process engineering; Thermal energy; Solar power; Nuclear engineering; Waste management; Environmental engineering; Meteorology; Engineering; Power (physics); Thermodynamics; Electrical engineering","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":[0.0005552634,0.0005547627,0.0004331649,0.0006126153,0.0004510941,0.000501817,0.0004270788,0.0004175752,0.001482635],"category_scores_gemma":[0.0006668345,0.0001615513,0.0006136771,0.0006113254,0.0002520584,0.0007268639,0.0002439689,0.000233663,0.0001769264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001284077,"about_ca_system_score_gemma":0.0004080534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009310691,"about_ca_topic_score_gemma":0.0162024,"domain_scores_codex":[0.9996643,0.00006189605,0.00001676508,0.00004826183,0.0001602564,0.00004841017],"domain_scores_gemma":[0.9994022,0.000307362,0.00005049608,0.00003374878,0.0001841538,0.00002202867],"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":[0.009236716,0.002080865,0.1314355,0.0008342701,0.0006100491,0.0004559323,0.0002416411,0.3895552,0.3525666,0.001111742,0.001047538,0.1108239],"study_design_scores_gemma":[0.0001602801,0.008149159,0.2105497,0.00003273513,0.0004644893,0.0001817707,0.0007913921,0.3492657,0.4282647,0.0009534305,0.001101835,0.00008488839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981436,0.00007831544,0.0005481575,0.00001034813,0.000003420857,0.00001752597,0.000188277,0.00001346096,0.000996853],"genre_scores_gemma":[0.9993315,0.00003440966,0.0002454867,0.000001994259,0.000001106854,0.000006538277,0.000107483,0.000003505971,0.0002680979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009310691,"threshold_uncertainty_score":0.01851302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0157570535539676,"score_gpt":0.2509299736023894,"score_spread":0.2351729200484218,"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."}}