{"id":"W4312417090","doi":"10.1007/978-3-031-05125-8_22","title":"A Wind Energy-Based Cogeneration System for Energy and Fresh Water Production","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in energy","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Cogeneration; Compressed air; Exergy; Environmental science; Wind power; Thermal energy; Marine engineering; Process engineering; Underwater; Energy (signal processing); Environmental engineering; Engineering; Waste management; Power (physics); Electricity generation; Mechanical engineering; Electrical engineering; Geology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002141592,0.0007729788,0.0006844442,0.0002802819,0.0004926807,0.00005874837,0.0003164091,0.0005239483,0.0006146556],"category_scores_gemma":[0.00003457306,0.000637707,0.000187862,0.0001091981,0.0002620284,0.0001585538,0.0004204589,0.000207935,0.000003862133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009288286,"about_ca_system_score_gemma":0.00003618225,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00402981,"about_ca_topic_score_gemma":0.0314186,"domain_scores_codex":[0.9966223,0.000114456,0.00059291,0.001403001,0.0006205923,0.0006467941],"domain_scores_gemma":[0.9988447,0.0001420178,0.0002443717,0.0006150019,0.00003764132,0.0001162586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006805928,0.0001940941,0.00009325703,0.0003059625,0.0004313753,0.0001423707,0.0005732054,0.4856066,0.06204797,0.3772205,0.005488507,0.06721552],"study_design_scores_gemma":[0.0007522239,0.0003840246,0.000006517458,0.0001279,0.0001441495,0.00004833172,0.000009487452,0.004069727,0.1981205,0.07439999,0.7208391,0.001098043],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.002956976,0.01659957,0.3982323,0.01065077,0.01441416,0.002364779,0.001507437,0.001641659,0.5516324],"genre_scores_gemma":[0.9681802,0.0001374291,0.001044852,0.001301951,0.001199443,0.0005211662,0.001190112,0.0002568699,0.02616797],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9652233,"threshold_uncertainty_score":0.9996074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01015274445545869,"score_gpt":0.1849468918397607,"score_spread":0.174794147384302,"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."}}