{"id":"W4389390549","doi":"10.1021/acs.langmuir.3c02405","title":"Predicting Impact Outcomes and Maximum Spreading of Drop Impact on Heated Nanostructures Using Machine Learning","year":2023,"lang":"en","type":"article","venue":"Langmuir","topic":"Fluid Dynamics and Heat Transfer","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Surface roughness; Materials science; Phase diagram; Mechanics; Surface finish; Nanofluid; Surface energy; Heat transfer; Nanotechnology; Phase (matter); Composite material; Chemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003765515,0.0004752387,0.0003607379,0.0005377872,0.0001574875,0.0004237427,0.0003610154,0.0004952491,0.0004012249],"category_scores_gemma":[0.001405455,0.0002020373,0.0004156945,0.0003172344,0.000252651,0.0007407382,0.0002617183,0.0004950773,0.0001365709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004752353,"about_ca_system_score_gemma":0.0002544587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001601529,"about_ca_topic_score_gemma":0.001825937,"domain_scores_codex":[0.9998692,0.00001380785,0.00000994817,0.00004677308,0.00004333909,0.00001690417],"domain_scores_gemma":[0.9994778,0.0002613458,0.0001113466,0.00004296589,0.00008206516,0.00002438962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004123183,0.0002955804,0.05954072,0.0002503011,0.00008576208,0.0004365808,0.0001088565,0.6985374,0.1777201,0.0009711719,0.0003219007,0.06131933],"study_design_scores_gemma":[0.000001853708,0.00003440545,0.004398122,0.000002168571,0.000004569085,0.00001464226,0.000008598927,0.979412,0.01592287,0.0001565693,0.00003862908,0.000005568497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9535374,0.0001719337,0.04521213,0.00003828494,0.000009600829,0.00002629803,0.0001393856,0.0002424527,0.0006225388],"genre_scores_gemma":[0.9933646,0.00006581466,0.006261911,0.000009284759,0.000003002626,0.00001386721,0.0001174262,0.000007216483,0.0001570227],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001601529,"threshold_uncertainty_score":0.003448129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01106085375014817,"score_gpt":0.2614460204299093,"score_spread":0.2503851666797612,"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."}}