{"id":"W1977851743","doi":"10.1504/ijex.2013.052544","title":"Dynamic exergetic performance assessment of an integrated solar pond","year":2013,"lang":"en","type":"article","venue":"International Journal of Exergy","topic":"Solar-Powered Water Purification Methods","field":"Energy","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"University of Ontario Institute of Technology","keywords":"Exergy; Solar pond; Environmental science; Solar energy; Exergy efficiency; Environmental engineering; Atmospheric sciences; Process engineering; Nuclear engineering; Meteorology; Engineering; Geology; Physics; 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":[0.0003696189,0.0004733787,0.0008826506,0.0003743965,0.0004934041,0.0006729586,0.0006375387,0.0005114021,0.001260531],"category_scores_gemma":[0.0005160999,0.0002362905,0.0004874915,0.0005667695,0.000404229,0.0008549515,0.0007635095,0.0004448082,0.0002372377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003774058,"about_ca_system_score_gemma":0.0004034377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001013886,"about_ca_topic_score_gemma":0.001370375,"domain_scores_codex":[0.9995664,0.00002813915,0.0000233552,0.00008028294,0.0002489765,0.0000528861],"domain_scores_gemma":[0.9997999,0.00004481439,0.00001865839,0.00003237237,0.00008264912,0.00002161773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004418638,0.0002507644,0.005054125,0.0002310666,0.00004290986,0.0001879099,0.00008349623,0.01358401,0.9646456,0.0001680733,0.00007240035,0.0152379],"study_design_scores_gemma":[0.00005139545,0.001106063,0.01864391,0.00001330303,0.00008118726,0.0001557737,0.0001614906,0.04859813,0.9295907,0.0002123224,0.00135632,0.00002931739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875919,0.0001267614,0.01107015,0.00001169773,0.00001105775,0.0000465564,0.0001371056,0.00009898472,0.0009057976],"genre_scores_gemma":[0.9953533,0.00009638777,0.003692602,0.000007288255,0.000002373024,0.00003009712,0.0001031161,0.00001176569,0.0007029913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001260531,"threshold_uncertainty_score":0.00421685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01257985329744647,"score_gpt":0.3197006105607619,"score_spread":0.3071207572633154,"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."}}