{"id":"W2905757330","doi":"10.1039/c8nr08763f","title":"Sink or float? Characterization of shell-stabilized bulk nanobubbles using a resonant mass measurement technique","year":2018,"lang":"en","type":"article","venue":"Nanoscale","topic":"Minerals Flotation and Separation Techniques","field":"Environmental Science","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Toronto Public Health","funders":"DOD Prostate Cancer Research Program; National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; National Foundation for Cancer Research; U.S. Department of Defense","keywords":"Bubble; Characterization (materials science); Sink (geography); Float (project management); Materials science; Shell (structure); Mechanics; Chemical physics; Nanotechnology; Computational physics; Physics; Composite material; Marine engineering; Engineering","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":[0.0001704944,0.0002063208,0.0002349944,0.0003071,0.0001965172,0.0002391215,0.0002167345,0.0002907931,0.0008908174],"category_scores_gemma":[0.0003190618,0.0001679864,0.00008288899,0.00007917601,0.0002386284,0.0004030815,0.0001719058,0.0003060942,0.0003817052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001445482,"about_ca_system_score_gemma":0.0001085927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005863009,"about_ca_topic_score_gemma":0.001101923,"domain_scores_codex":[0.9999142,0.000007472376,0.000004919534,0.00002857669,0.00003097034,0.0000139226],"domain_scores_gemma":[0.999856,0.00004251531,0.00003345577,0.00001120342,0.00004137919,0.00001535605],"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":[0.0000155226,0.000004195087,0.00008381513,0.00000954684,8.948652e-7,0.00000814059,0.00001805631,0.00003334212,0.9990803,0.00004217581,0.0000165538,0.0006874095],"study_design_scores_gemma":[0.000004808086,0.00005469653,0.001271092,0.000002331898,0.000002752659,0.00003281121,0.00003485488,0.003005727,0.995041,0.00005514351,0.0004893166,0.000005458593],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836151,0.0005547144,0.0143455,0.0001036436,0.0000194437,0.00003750886,0.0001508098,0.0002144286,0.0009589469],"genre_scores_gemma":[0.9837727,0.000303817,0.01308434,0.00007967767,0.000009489877,0.00005413203,0.0001941288,0.00007488823,0.002426839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008908174,"threshold_uncertainty_score":0.002980113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04044805399716173,"score_gpt":0.2771396706701993,"score_spread":0.2366916166730376,"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."}}