{"id":"W2793523987","doi":"10.1039/c7sm02523h","title":"Diffusive interaction of multiple surface nanobubbles: shrinkage, growth, and coarsening","year":2018,"lang":"en","type":"article","venue":"Soft Matter","topic":"Minerals Flotation and Separation Techniques","field":"Environmental Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"H2020 European Research Council; Ministerie van Onderwijs, Cultuur en Wetenschap; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Australian Research Council; Partnership for Advanced Computing in Europe AISBL; Stichting voor Fundamenteel Onderzoek der Materie","keywords":"Bubble; Diffusion; Surface (topology); Chemical physics; Surface diffusion; Dissolution; Shrinkage; Materials science; Nanoscopic scale; Boundary (topology); Nanotechnology; Mechanics; Chemistry; Physics; Thermodynamics; Adsorption; Composite material; Physical chemistry; Mathematics","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":[0.0001566541,0.0002583417,0.0003662303,0.0003729486,0.0003484277,0.0004783276,0.0004054447,0.0004498571,0.0006318586],"category_scores_gemma":[0.0006351661,0.0001945362,0.0003162077,0.0001129783,0.0006087271,0.0006617009,0.0006852252,0.0004903086,0.00008728032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005834514,"about_ca_system_score_gemma":0.0003079374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002444415,"about_ca_topic_score_gemma":0.001786219,"domain_scores_codex":[0.9998658,0.00001070764,0.000005482655,0.00003846723,0.00004506618,0.00003451563],"domain_scores_gemma":[0.9997531,0.0001040774,0.00004460528,0.00002187111,0.00002807851,0.00004831797],"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":[0.0001260874,0.00009597909,0.002287803,0.0001122619,0.00001972524,0.0005112759,0.0002979473,0.08921863,0.8777854,0.01810089,0.0001405852,0.01130342],"study_design_scores_gemma":[0.00002787357,0.00008208396,0.002310301,0.000007178315,0.000009939612,0.0001353214,0.00005889624,0.8410679,0.1516587,0.003900254,0.0007210154,0.00002048556],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9454389,0.0005043924,0.05206237,0.0001231244,0.00002281164,0.0000283646,0.00001938674,0.00008332001,0.001717392],"genre_scores_gemma":[0.9933739,0.0001218057,0.005417216,0.00001396111,0.000006639656,0.00001525958,0.00001554827,0.00001370038,0.001022104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002444415,"threshold_uncertainty_score":0.004860342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01048548669245079,"score_gpt":0.2527770197671916,"score_spread":0.2422915330747409,"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."}}