{"id":"W2290767110","doi":"10.1090/proc/13324","title":"Davies’ method for anomalous diffusions","year":2016,"lang":"en","type":"preprint","venue":"Proceedings of the American Mathematical Society","topic":"Geometric Analysis and Curvature Flows","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Institute for the Mathematical Sciences; University of British Columbia","funders":"National Science Foundation","keywords":"Heat kernel; Diagonal; Singularity; Mathematics; Cutoff; Gaussian; Kernel (algebra); Sobolev space; Upper and lower bounds; Energy (signal processing); Computation; Perturbation (astronomy); Applied mathematics; Pure mathematics; Mathematical analysis; Statistical physics; Physics; Algorithm; Geometry; Quantum mechanics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001526029,0.0005259229,0.001764109,0.00007821174,0.0002338784,0.00009904285,0.001526929,0.0002799372,0.00008410682],"category_scores_gemma":[0.00236839,0.0002833645,0.002715109,0.0007973997,0.0005699469,0.00006758441,0.001790789,0.0006127802,0.000007915949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001308994,"about_ca_system_score_gemma":0.0000847398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008520342,"about_ca_topic_score_gemma":2.889985e-7,"domain_scores_codex":[0.996974,0.00002624251,0.0009796978,0.0006637757,0.0007994846,0.0005568155],"domain_scores_gemma":[0.9945526,0.001757878,0.0022542,0.0005561658,0.000720777,0.0001583763],"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":[0.0001083063,0.002150301,0.001513943,0.01318757,0.004729591,3.135311e-7,0.006241993,0.000003310531,0.01667007,0.5962926,0.3485464,0.01055572],"study_design_scores_gemma":[0.0002878672,0.00007261361,0.0002354641,0.0005542462,0.001287193,0.000004956859,0.001476286,0.002615309,0.00146028,0.9901223,0.001445823,0.0004376834],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3951367,0.0003229677,0.5655587,0.0127784,0.0005425321,0.004802806,0.0004660932,0.0004410133,0.01995085],"genre_scores_gemma":[0.1936161,0.00008706031,0.8015682,0.0005034678,0.0005606126,0.0005642005,0.000004191366,0.0001492936,0.002946798],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3938298,"threshold_uncertainty_score":0.9999619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03235437747878731,"score_gpt":0.3335685291230077,"score_spread":0.3012141516442204,"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."}}