{"id":"W2964544192","doi":"10.11159/htff19.112","title":"Fast Energy Transport in Droplet Evaporation","year":2019,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Electrohydrodynamics and Fluid Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Evaporation; Energy transport; Energy (signal processing); Environmental science; Computer science; Engineering physics; Physics; Meteorology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001005573,0.0002148324,0.0002984422,0.0001303616,0.00001647086,0.00003734169,0.0002347148,0.0001031245,0.00001765668],"category_scores_gemma":[0.000009568249,0.0001877135,0.00005805089,0.0002600081,0.00001943046,0.0001160597,0.0000469891,0.0001774863,0.000001031573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005866684,"about_ca_system_score_gemma":0.000006136936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008953087,"about_ca_topic_score_gemma":0.000009040601,"domain_scores_codex":[0.9990181,0.000001561624,0.0003263201,0.0002226999,0.0001635049,0.0002677577],"domain_scores_gemma":[0.9997258,0.00001850558,0.00005112419,0.000110625,0.00003524088,0.00005865931],"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":[0.00003347922,0.00001803361,0.00004803267,0.0002045443,0.00001615217,3.904367e-7,0.000004533697,0.004522681,0.9688592,0.02613597,0.00003568738,0.0001212954],"study_design_scores_gemma":[0.0002983957,0.00002332241,0.00002596248,0.0001687575,0.00001103371,0.000002690943,0.000005341843,0.2605269,0.7380867,0.0003026583,0.0003651786,0.000183052],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998374,0.000008543215,0.00000822052,0.00004862418,0.0007612182,0.000150057,0.00001379579,0.0001113395,0.000524221],"genre_scores_gemma":[0.9993423,0.00007554736,0.0002525797,0.00002197336,0.00006971925,0.00002410355,0.000008663339,0.00004923359,0.0001559136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2560042,"threshold_uncertainty_score":0.7654734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002208433120575834,"score_gpt":0.1604470104528974,"score_spread":0.1582385773323216,"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."}}