{"id":"W3101611055","doi":"10.1214/ecp.v15-1521","title":"Lipschitz percolation","year":2010,"lang":"en","type":"article","venue":"Electronic Communications in Probability","topic":"Stochastic processes and statistical mechanics","field":"Mathematics","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Deutsche Forschungsgemeinschaft; Microsoft Research","keywords":"Lipschitz continuity; Mathematics; Percolation (cognitive psychology); Combinatorics; Constant (computer programming); Mathematical physics; Function (biology); Discrete mathematics; Mathematical analysis; Computer science","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":[0.001169781,0.0007370225,0.0009641397,0.001362981,0.001317738,0.001791396,0.001570687,0.001540433,0.00855952],"category_scores_gemma":[0.01288275,0.0004213811,0.001162043,0.0007488457,0.002453864,0.003072629,0.002686288,0.002422222,0.00116321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001763898,"about_ca_system_score_gemma":0.001040787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002052192,"about_ca_topic_score_gemma":0.001787713,"domain_scores_codex":[0.999005,0.000246375,0.00003347403,0.0002525428,0.0002939976,0.0001686175],"domain_scores_gemma":[0.9927899,0.004218245,0.0008474601,0.0006178806,0.0006516089,0.0008748489],"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":[0.00005983916,0.00002397426,0.0006476154,0.000130598,0.000027182,0.0002357818,0.0001052492,0.01462032,0.001684228,0.9711746,0.005005789,0.006284781],"study_design_scores_gemma":[0.000049082,0.00007171938,0.00113944,0.00004818746,0.00004364099,0.0005800559,0.00006976957,0.1752386,0.002096984,0.8079147,0.01270874,0.00003902771],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1645268,0.004416814,0.6687173,0.006194451,0.0005270201,0.0001701653,0.001512947,0.0009828663,0.1529517],"genre_scores_gemma":[0.898548,0.002392106,0.05727969,0.001233237,0.0004662127,0.0002852229,0.0007221347,0.0002754112,0.03879796],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00855952,"threshold_uncertainty_score":0.02863449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05723509872802925,"score_gpt":0.3651894397726863,"score_spread":0.3079543410446571,"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."}}