{"id":"W4387310361","doi":"10.1063/5.0167659","title":"Understanding under-liquid drop spreading using dynamic contact angle modeling","year":2023,"lang":"en","type":"article","venue":"Physics of Fluids","topic":"Surface Modification and Superhydrophobicity","field":"Materials Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Physics; Scaling; Drop (telecommunication); Scaling law; Mechanics; Viscosity; Contact angle; Inertial frame of reference; Viscous liquid; Thermodynamics; Classical mechanics; Geometry","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":[0.0001092573,0.0004078786,0.0002996938,0.0002842262,0.0001675238,0.0004805454,0.0004263696,0.0005156276,0.000907906],"category_scores_gemma":[0.0003720495,0.0001257414,0.0003342486,0.0002025371,0.000198617,0.0006608973,0.0002438342,0.0003698996,0.0001824228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000345178,"about_ca_system_score_gemma":0.0002960714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003718697,"about_ca_topic_score_gemma":0.001816502,"domain_scores_codex":[0.9999305,0.000007641427,0.000004269383,0.00001360151,0.00002918629,0.00001475032],"domain_scores_gemma":[0.9998512,0.00005998228,0.00002801504,0.00002288707,0.000027641,0.00001017983],"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":[0.0000379853,0.0001266433,0.00356737,0.00009043876,0.00002414649,0.0003566305,0.00009732634,0.6241362,0.3509859,0.004213385,0.0001470651,0.01621686],"study_design_scores_gemma":[0.000001827933,0.0000148153,0.000471087,0.000001292218,0.000002261533,0.0000202407,0.000006567935,0.9884896,0.01053453,0.0002721006,0.0001819959,0.000003690484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7891123,0.0003443769,0.203481,0.0001475913,0.0000259188,0.00006998951,0.000201865,0.0002825065,0.006334451],"genre_scores_gemma":[0.9850287,0.0002657366,0.01392909,0.00001805445,0.00000620152,0.00002476851,0.00009172365,0.00002310206,0.0006125637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003718697,"threshold_uncertainty_score":0.007394135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1875520245725724,"score_gpt":0.3212762083784087,"score_spread":0.1337241838058363,"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."}}