{"id":"W4393374799","doi":"10.1016/j.nanoen.2024.109560","title":"Machine-assisted quantification of droplet boiling upon multiple solid materials","year":2024,"lang":"en","type":"article","venue":"Nano Energy","topic":"Fluid Dynamics and Heat Transfer","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Boiling; Materials science; Superhydrophilicity; Heat transfer; Wetting; Nanofluid; Boiling heat transfer; Leidenfrost effect; Range (aeronautics); Mechanics; Nucleate boiling; Thermodynamics; Nanotechnology; Composite material; Heat transfer coefficient","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":[0.0002437822,0.0002867764,0.0003165356,0.0004333645,0.0002948309,0.0004922264,0.0004460961,0.0005005608,0.002216105],"category_scores_gemma":[0.0005334648,0.0001994486,0.0001759114,0.0002838847,0.0006067436,0.0005809593,0.0004110914,0.00073006,0.0003709458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004161135,"about_ca_system_score_gemma":0.0002227793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002980934,"about_ca_topic_score_gemma":0.0006793814,"domain_scores_codex":[0.9996756,0.00003212001,0.000007821011,0.00008648343,0.0001524701,0.00004548204],"domain_scores_gemma":[0.9997662,0.0001008038,0.00003998559,0.00003057529,0.0000435447,0.0000188568],"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":[0.00006588185,0.00002158437,0.0002652804,0.00002289805,0.000004341953,0.00001745337,0.00002789914,0.0001796671,0.9959997,0.0002344456,0.00009023232,0.003070554],"study_design_scores_gemma":[0.000006731849,0.0001012208,0.00152436,0.000003055515,0.000005050584,0.000032944,0.0000210301,0.0144057,0.9831569,0.00008738515,0.0006466768,0.000009137485],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9384052,0.0004187352,0.05706135,0.0001355122,0.0001213057,0.00008643814,0.0002898134,0.0004389293,0.003042808],"genre_scores_gemma":[0.982996,0.0001669718,0.0151032,0.0000640228,0.00003334144,0.00005914532,0.0001221118,0.00005195965,0.001403235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002216105,"threshold_uncertainty_score":0.007413566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01145767090637428,"score_gpt":0.2252545616011884,"score_spread":0.2137968906948141,"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."}}