{"id":"W4408020458","doi":"10.1016/j.susmat.2025.e01300","title":"Integrating multiple cold plasma generators and Bernoulli-driven microbubble formation for large-volume water treatment","year":2025,"lang":"en","type":"article","venue":"Sustainable materials and technologies","topic":"Plasma Applications and Diagnostics","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Research Chairs","keywords":"Bernoulli's principle; Plasma; Volume (thermodynamics); Nuclear engineering; Mechanics; Materials science; Environmental science; Physics; Thermodynamics; Engineering; Nuclear physics","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":[0.0001051409,0.0001439377,0.0002576456,0.0001512318,0.0002729685,0.0001152051,0.00004543345,0.0001559694,0.00000546443],"category_scores_gemma":[0.0001864746,0.00009597832,0.00002145599,0.00008076325,0.00006007542,0.0001215713,0.0001180737,0.00003616576,0.000002041489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001073147,"about_ca_system_score_gemma":0.00003627531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006782515,"about_ca_topic_score_gemma":0.00001555218,"domain_scores_codex":[0.9992335,0.000007909892,0.0002092766,0.0001998004,0.00003447629,0.0003150584],"domain_scores_gemma":[0.9995818,0.0000652012,0.00004476173,0.0001624129,0.0001237432,0.00002208754],"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":[0.0001377799,0.0001830506,0.004614517,0.001147645,0.00008686387,0.00001816352,0.0003000743,0.000008333482,0.8868013,0.1003534,0.002547425,0.003801482],"study_design_scores_gemma":[0.001498173,0.0002204237,0.00009719724,0.00005219475,0.00007710134,0.000009130546,0.006456979,0.0007891119,0.9044059,0.002481895,0.08381197,0.00009993049],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937716,0.0002956626,0.002233186,0.002014213,0.00004343489,0.001207507,0.00009420718,0.000250704,0.00008953346],"genre_scores_gemma":[0.9885231,0.0004362741,0.008263515,0.00005425459,0.00001398937,0.000720091,0.0001274056,0.00001089653,0.001850512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09787147,"threshold_uncertainty_score":0.3913882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006759879905466484,"score_gpt":0.2361400927357912,"score_spread":0.2293802128303247,"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."}}