{"id":"W1964106924","doi":"10.1002/qua.22134","title":"Improving reptation quantum Monte Carlo","year":2009,"lang":"en","type":"article","venue":"International Journal of Quantum Chemistry","topic":"Quantum, superfluid, helium dynamics","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reptation; Quantum Monte Carlo; Monte Carlo method; Statistical physics; Hamiltonian (control theory); Electron; Diffusion Monte Carlo; Node (physics); Hybrid Monte Carlo; Physics; Population; Quantum; Mathematics; Quantum mechanics; Mathematical optimization; Markov chain Monte Carlo; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003122444,0.000593261,0.0009180496,0.0008581218,0.0005464926,0.0007978753,0.002353831,0.001091079,0.002920034],"category_scores_gemma":[0.01290958,0.0004491784,0.0007161433,0.0008010463,0.0008794977,0.001222216,0.001520649,0.001494146,0.0007727414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001141742,"about_ca_system_score_gemma":0.001165628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009195822,"about_ca_topic_score_gemma":0.007556083,"domain_scores_codex":[0.9981712,0.0009057586,0.00006086041,0.0001932775,0.0005473714,0.0001215691],"domain_scores_gemma":[0.9918391,0.004371279,0.0004724332,0.001612668,0.001540654,0.0001639298],"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":[0.0003150009,0.0001091636,0.002280923,0.00008227397,0.00009557008,0.00007799682,0.000114951,0.8780869,0.003822111,0.03333257,0.002058506,0.07962408],"study_design_scores_gemma":[0.000008350877,0.00001203198,0.00006458502,0.000002365418,0.000003365145,0.000005915173,0.000002014385,0.9968253,0.0006141498,0.002168953,0.0002891931,0.000003827337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03565334,0.000213045,0.9583652,0.0002013485,0.00005473226,0.00009036467,0.00007317172,0.002181042,0.003167795],"genre_scores_gemma":[0.4910946,0.0001229526,0.5059661,0.0002515458,0.00005718384,0.0002171629,0.0002577574,0.0004705327,0.001562085],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009195822,"threshold_uncertainty_score":0.01828462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006435594610609676,"score_gpt":0.2531320184901277,"score_spread":0.2466964238795181,"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."}}