{"id":"W2026312458","doi":"10.1002/cpa.20091","title":"Characterization of sub‐Gaussian heat kernel estimates on strongly recurrent graphs","year":2005,"lang":"en","type":"preprint","venue":"Communications on Pure and Applied Mathematics","topic":"Geometry and complex manifolds","field":"Mathematics","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Characterization (materials science); Heat kernel; Gaussian; Kernel (algebra); Mathematics; Statistical physics; Combinatorics; Computer science; Materials science; Physics; Nanotechnology; Mathematical analysis; 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":[0.001857691,0.0007545344,0.0007877497,0.002572494,0.0004491323,0.001664399,0.001214971,0.001135745,0.00356126],"category_scores_gemma":[0.01019025,0.0004026516,0.0007441406,0.0006369781,0.001780258,0.003003323,0.00163191,0.001550086,0.0005454534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007817418,"about_ca_system_score_gemma":0.000260914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006153305,"about_ca_topic_score_gemma":0.0004330204,"domain_scores_codex":[0.9992336,0.0002123754,0.00003726463,0.0001587349,0.000210206,0.0001477879],"domain_scores_gemma":[0.9925288,0.00363181,0.001431056,0.0006766879,0.000993037,0.0007386528],"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":[0.0001653461,0.00006848625,0.002354642,0.0001207636,0.00005162519,0.0003187512,0.0004197853,0.01964624,0.02016059,0.9470314,0.001975216,0.007687186],"study_design_scores_gemma":[0.00002026464,0.0001040264,0.002902109,0.00003427483,0.0000375559,0.0003562195,0.0001429603,0.4796577,0.005448709,0.5095571,0.001680383,0.00005860722],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.538241,0.0007210021,0.4454708,0.0008811547,0.00009451621,0.00005720181,0.0002864592,0.0005191362,0.01372881],"genre_scores_gemma":[0.9848315,0.0003825757,0.01045275,0.0001306911,0.0001391903,0.00004765677,0.0001609531,0.0001245989,0.003730192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00356126,"threshold_uncertainty_score":0.0119136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06599598363553125,"score_gpt":0.3128781166533093,"score_spread":0.246882133017778,"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."}}