{"id":"W2030014435","doi":"10.1016/j.ijthermalsci.2007.01.012","title":"Exergetic performance analysis of a solar pond","year":2007,"lang":"en","type":"article","venue":"International Journal of Thermal Sciences","topic":"Solar-Powered Water Purification Methods","field":"Energy","cited_by":69,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Exergy; Solar pond; Environmental science; Convection; Exergy efficiency; Thermal energy storage; Solar energy; Atmospheric sciences; Meteorology; Geology; Thermodynamics; Physics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003295622,0.00007889206,0.0002005598,0.0008969674,0.00005632241,0.00004870549,0.001042319,0.00004008787,0.0005736063],"category_scores_gemma":[0.00018541,0.00005807155,0.0001986575,0.0008348339,0.000209918,0.000421545,0.00004760125,0.0001093704,0.000008619778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005565794,"about_ca_system_score_gemma":0.00006700662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008633335,"about_ca_topic_score_gemma":0.00002161261,"domain_scores_codex":[0.9980727,0.00008057377,0.0006182362,0.0001136086,0.0009520254,0.0001627855],"domain_scores_gemma":[0.9984996,0.0002002734,0.0006242293,0.0001007034,0.0005058639,0.00006937569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000478609,0.0003048999,0.3671454,0.000008806195,0.002572811,0.00005490332,0.003242655,0.1213237,0.3387302,0.007427135,0.00007980142,0.158631],"study_design_scores_gemma":[0.0004612314,0.0002334625,0.7648288,0.00004609169,0.0002919544,0.00006687506,0.0004745966,0.009355054,0.2185774,0.0008345899,0.004647948,0.0001820061],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848529,0.0001423473,0.005974431,0.0002878468,0.0008144486,0.00001948338,0.000002366982,0.000006392085,0.007899824],"genre_scores_gemma":[0.9867547,0.00002901626,0.01279537,0.00009204855,0.0001697068,3.406301e-7,9.64152e-7,0.000004326771,0.0001535156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3976834,"threshold_uncertainty_score":0.6280586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0310016363595566,"score_gpt":0.3434108229297775,"score_spread":0.3124091865702209,"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."}}