{"id":"W1983572889","doi":"10.1063/1.4803118","title":"On the origin and convergence of a post-quantization constrained propagator for path integral simulations of rigid bodies","year":2013,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Quantum, superfluid, helium dynamics","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Propagator; Path integral formulation; Estimator; Quantization (signal processing); Convergence (economics); Path integral Monte Carlo; Applied mathematics; Mathematics; Angular momentum; Statistical physics; Rigid rotor; Monte Carlo method; Physics; Classical mechanics; Rotor (electric); Quantum mechanics; Algorithm; Quantum; Mathematical 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":[0.003842173,0.0005016029,0.0005239554,0.0008393967,0.0009713956,0.001187527,0.001620458,0.0009706476,0.003370248],"category_scores_gemma":[0.01380163,0.0004101846,0.0003925706,0.0006285171,0.002856882,0.002092125,0.001761667,0.001853477,0.0003841282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007345803,"about_ca_system_score_gemma":0.001665668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001940535,"about_ca_topic_score_gemma":0.001976877,"domain_scores_codex":[0.999351,0.0002990598,0.00002363749,0.00003887713,0.0002399019,0.00004755092],"domain_scores_gemma":[0.9945264,0.003886403,0.0003576953,0.0005561209,0.0005097462,0.0001635469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004471224,0.00005188739,0.0004778896,0.00009633494,0.00001510842,0.0001092432,0.000217535,0.2713092,0.003006343,0.7098852,0.0004965173,0.01429002],"study_design_scores_gemma":[0.000007909098,0.00001528289,0.00008049965,0.00001087768,0.000001835767,0.00001285964,0.0000112503,0.9567151,0.0006827218,0.0420766,0.0003763703,0.000008792644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04321627,0.0001100282,0.9498471,0.0003954051,0.00005359704,0.00009277924,0.00004302411,0.0001600978,0.006081717],"genre_scores_gemma":[0.5202939,0.0003935214,0.4748091,0.0002187381,0.00006501818,0.0006025251,0.00009441478,0.0006147358,0.002908184],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003842173,"threshold_uncertainty_score":0.02031958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01247355389508805,"score_gpt":0.2476111119985716,"score_spread":0.2351375581034836,"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."}}