{"id":"W2256665692","doi":"10.1080/10618600.2012.723569","title":"An Adaptive Interacting Wang–Landau Algorithm for Automatic Density Exploration","year":2012,"lang":"en","type":"article","venue":"Journal of Computational and Graphical Statistics","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Algorithm; Artificial intelligence; Statistical physics; Physics","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":[0.00223878,0.000691916,0.0008437282,0.001200528,0.0008662281,0.001055178,0.001971079,0.001188963,0.004408675],"category_scores_gemma":[0.007644217,0.0004967023,0.0007132426,0.001004336,0.001178465,0.001409217,0.001859515,0.001275521,0.001027823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009059544,"about_ca_system_score_gemma":0.002039743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003110958,"about_ca_topic_score_gemma":0.005532682,"domain_scores_codex":[0.9992177,0.0002953852,0.00004780624,0.0001293927,0.0002493982,0.00006024085],"domain_scores_gemma":[0.9978503,0.001337449,0.0001544481,0.0002629682,0.0002941926,0.0001007396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002421426,0.0001165674,0.002190711,0.0001295068,0.00009030227,0.0002324955,0.0003494341,0.532847,0.008673608,0.1736545,0.003327565,0.2781461],"study_design_scores_gemma":[0.00001771729,0.00001454039,0.00006390241,0.000005150291,0.000004594673,0.00002457826,0.000007062806,0.9794827,0.0009187278,0.01859177,0.0008607194,0.000008493161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003221219,0.00003167807,0.9957085,0.0000469865,0.00001065396,0.00002964667,0.00001085792,0.0003148692,0.0006256716],"genre_scores_gemma":[0.08223187,0.00004777722,0.91544,0.00006684082,0.00001823117,0.000209566,0.00006553675,0.0001577895,0.001762288],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004408675,"threshold_uncertainty_score":0.01474851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07624063086788722,"score_gpt":0.3818334136523043,"score_spread":0.305592782784417,"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."}}