{"id":"W3170629259","doi":"10.1021/acssuschemeng.1c00785","title":"Metals Recovery from Seawater Desalination Brines: Technologies, Opportunities, and Challenges","year":2021,"lang":"en","type":"article","venue":"ACS Sustainable Chemistry & Engineering","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":132,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Sustainability; Desalination; Resource recovery; Brine; Seawater; Environmental science; Resource (disambiguation); Waste management; Natural resource economics; Environmental planning; Business; Environmental resource management; Environmental engineering; Wastewater; Engineering; Oceanography; Geology; Ecology; Computer science; Economics; Chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.00008689544,0.0002000454,0.0001917402,0.00005356542,0.00005562009,0.0001113124,0.00009424786,0.0001750523,0.0000774412],"category_scores_gemma":[0.0001861446,0.0002334654,0.00003078248,0.0001478267,0.00001827961,0.0004662439,0.00006414793,0.0001800234,0.000002999768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001115284,"about_ca_system_score_gemma":0.00005192835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000940893,"about_ca_topic_score_gemma":0.000001252771,"domain_scores_codex":[0.9991317,0.000005078011,0.0002120753,0.0002381018,0.0001166965,0.0002963291],"domain_scores_gemma":[0.9994419,0.00007079615,0.00002701945,0.0002277491,0.0001709349,0.00006157287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001555813,0.00008632817,0.00005023084,0.007413231,0.0006449023,0.001270706,0.0008914761,0.09835813,0.8573461,0.006442525,0.002126507,0.02535431],"study_design_scores_gemma":[0.0001626225,0.000004039484,0.00004616277,0.00003830543,0.00002549578,0.00005902669,0.00564565,0.003278114,0.6876763,0.0004731647,0.3023057,0.0002854341],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7840436,0.1602648,0.01206613,0.003308616,0.0004118695,0.000283499,0.00003497757,0.005311769,0.03427475],"genre_scores_gemma":[0.9560779,0.0327735,0.001126811,0.00002139607,0.00009624556,0.00006654184,0.0001564944,0.00006285081,0.00961831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3001792,"threshold_uncertainty_score":0.9520444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02433439551261418,"score_gpt":0.2065121677314747,"score_spread":0.1821777722188606,"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."}}