{"id":"W3009326789","doi":"10.4171/jst/382","title":"Spectral invariants of Dirichlet-to-Neumann operators on surfaces","year":2021,"lang":"en","type":"preprint","venue":"Journal of Spectral Theory","topic":"Advanced Mathematical Modeling in Engineering","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Engineering and Physical Sciences Research Council","keywords":"Mathematics; Geodesic; Constant curvature; Mathematical analysis; Invariant (physics); Boundary (topology); Dirichlet distribution; Mean curvature; Constant (computer programming); Eigenvalues and eigenvectors; Curvature; Spectrum (functional analysis); Dirichlet eigenvalue; Pure mathematics; Parametric statistics; Dirichlet boundary condition; Boundary value problem; Geometry; Mathematical physics; Physics; Dirichlet's principle; Quantum mechanics","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":[0.0006269374,0.0008479297,0.0004692571,0.003310336,0.0006408234,0.001499252,0.0007845964,0.0007678955,0.00317679],"category_scores_gemma":[0.00279984,0.0002472074,0.0005111918,0.0007206145,0.00236226,0.0027243,0.001876207,0.001285771,0.0005705672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000752985,"about_ca_system_score_gemma":0.0003579778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000341718,"about_ca_topic_score_gemma":0.0002702696,"domain_scores_codex":[0.9996105,0.0000859161,0.00001915501,0.0000590263,0.0001537934,0.00007156958],"domain_scores_gemma":[0.9990165,0.0002799559,0.0001659264,0.0001047187,0.0002546046,0.0001782574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003918763,0.00006260601,0.0004607833,0.00004579646,0.000007035168,0.0001504654,0.0002880146,0.008926855,0.01040967,0.9717885,0.00051474,0.00730627],"study_design_scores_gemma":[0.00001476277,0.0000438522,0.0009049402,0.00002522713,0.000005050755,0.0001993966,0.0001474447,0.1195801,0.003615884,0.8745373,0.0008934181,0.00003249868],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.794404,0.0003778113,0.164883,0.0005723353,0.0001194762,0.00004335974,0.0001071101,0.0003566837,0.03913628],"genre_scores_gemma":[0.9838095,0.0002062093,0.01037845,0.00006684185,0.0001382111,0.0000323599,0.0001006205,0.0001235848,0.005144253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003310336,"threshold_uncertainty_score":0.01062739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02152055453796037,"score_gpt":0.2710505219092181,"score_spread":0.2495299673712577,"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."}}