{"id":"W4386127155","doi":"10.32920/24026673.v1","title":"Biomedical nanobubbles and opportunities for microfluidics","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Minerals Flotation and Separation Techniques","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; St. Michael's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Microfluidics; Biomedicine; Nanotechnology; Toolbox; Materials science; Computer science; Bioinformatics; Biology","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":[0.001715761,0.0008335261,0.0009087845,0.001174807,0.0009344073,0.002674681,0.0009724351,0.002181697,0.006215947],"category_scores_gemma":[0.001518656,0.000633984,0.0006663094,0.00081413,0.002397218,0.005658499,0.002152596,0.002774836,0.002490568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001408407,"about_ca_system_score_gemma":0.001232036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004076399,"about_ca_topic_score_gemma":0.0003969627,"domain_scores_codex":[0.9991781,0.0001660231,0.00004166488,0.0001876316,0.0003268451,0.00009971959],"domain_scores_gemma":[0.9990977,0.0004242287,0.00007363813,0.00009693213,0.0001885318,0.0001189736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000199322,0.0001820488,0.0004678418,0.003004609,0.0000576043,0.000373134,0.000623593,0.004290082,0.1758536,0.5276424,0.02695918,0.2603466],"study_design_scores_gemma":[0.00005305981,0.0002820931,0.0004508908,0.0006350582,0.00002843689,0.0003924977,0.0002198683,0.009121674,0.09860052,0.1704815,0.7196233,0.0001111321],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02214534,0.6043337,0.2486285,0.04210478,0.0087662,0.0001976355,0.0005248484,0.002345873,0.07095312],"genre_scores_gemma":[0.242171,0.4564139,0.2392823,0.01063416,0.006609727,0.0006194026,0.00072097,0.0005350653,0.04301343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006215947,"threshold_uncertainty_score":0.02079445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1354543356969775,"score_gpt":0.3222758256202104,"score_spread":0.1868214899232329,"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."}}