{"id":"W4318719524","doi":"10.48550/arxiv.2301.13148","title":"Realistic pattern formations on surfaces by adding arbitrary roughness","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Adhesion, Friction, and Surface Interactions","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Youth Science Foundation","keywords":"Superposition principle; Discretization; Surface finish; Amplitude; Surface (topology); Eigenvalues and eigenvectors; Mathematics; Generalization; Mathematical analysis; Parametric statistics; Surface roughness; Operator (biology); Laplace transform; Rough surface; Geometry; Optics; Physics; Materials science; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002167283,0.0003307939,0.0003780395,0.0004090768,0.0003717611,0.0008434255,0.0004632321,0.0009751391,0.001072384],"category_scores_gemma":[0.0009634161,0.0003124374,0.0003930434,0.0002886486,0.0009393159,0.0006112512,0.000578013,0.0005192128,0.0001929562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004063619,"about_ca_system_score_gemma":0.0002179227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006621239,"about_ca_topic_score_gemma":0.0004555323,"domain_scores_codex":[0.999767,0.00004189814,0.00001054183,0.00004470752,0.00007478237,0.00006118817],"domain_scores_gemma":[0.9995983,0.0001505257,0.0000589583,0.000110161,0.00003982183,0.00004222719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000172119,0.0002103815,0.003467144,0.0001755844,0.00007585591,0.001167475,0.0004524855,0.5559067,0.3558912,0.06780463,0.001060557,0.01361589],"study_design_scores_gemma":[0.00006317729,0.0002209234,0.003864196,0.00001373184,0.00002462209,0.0004170803,0.0001936794,0.9353042,0.03693245,0.02037783,0.002533552,0.00005448363],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9014053,0.0001256373,0.09151381,0.0002564333,0.00006471411,0.00004101899,0.00006652397,0.00024159,0.006285028],"genre_scores_gemma":[0.9880377,0.00006710858,0.01057924,0.00002925707,0.00001055838,0.00002635896,0.00004057466,0.00001996308,0.001189225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001072384,"threshold_uncertainty_score":0.003587484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06964152855166031,"score_gpt":0.1930737538198268,"score_spread":0.1234322252681665,"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."}}