{"id":"W4402640583","doi":"10.1021/acsenergylett.4c02045","title":"Unifying Efficiency Metrics for Solar Evaporation and Thermal Desalination","year":2024,"lang":"en","type":"article","venue":"ACS Energy Letters","topic":"Solar-Powered Water Purification Methods","field":"Energy","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of New Brunswick","funders":"Chevron; U.S. Department of Energy","keywords":"Desalination; Evaporation; Environmental science; Thermal; Solar desalination; Process engineering; Low-temperature thermal desalination; Engineering physics; Materials science; Chemistry; Engineering; Meteorology; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004026762,0.0009946779,0.0008511263,0.004184053,0.000545062,0.002223759,0.001001861,0.0007506423,0.001608353],"category_scores_gemma":[0.008325418,0.0002553113,0.0009504175,0.002992966,0.001091253,0.003853996,0.001711942,0.001112535,0.0005979186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001377615,"about_ca_system_score_gemma":0.0008115674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001579908,"about_ca_topic_score_gemma":0.0016736,"domain_scores_codex":[0.9979048,0.0004367147,0.0001626604,0.0002677687,0.001060212,0.0001679716],"domain_scores_gemma":[0.996673,0.001386819,0.0004496027,0.0006326846,0.0007735843,0.00008427153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000453559,0.0004124845,0.04258988,0.001480592,0.0002535375,0.0002248822,0.0006515299,0.2331503,0.1123478,0.2008225,0.00597791,0.4016349],"study_design_scores_gemma":[0.00004101149,0.00108574,0.04193066,0.0003178815,0.000157867,0.0003786289,0.0008525889,0.5265147,0.2732393,0.1118863,0.0433496,0.0002457228],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2533503,0.006415401,0.6970411,0.001034476,0.0002507593,0.000355268,0.001385606,0.002012486,0.03815467],"genre_scores_gemma":[0.9069313,0.001668965,0.08740672,0.00009831387,0.00005304652,0.0002408588,0.0009722563,0.0003082002,0.002320291],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004184053,"threshold_uncertainty_score":0.02129579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02836930115234878,"score_gpt":0.2875182176149416,"score_spread":0.2591489164625929,"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."}}