{"id":"W2095020444","doi":"10.1021/ct050302x","title":"Distributed Replica Sampling","year":2006,"lang":"en","type":"article","venue":"Journal of Chemical Theory and Computation","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto; University of New Brunswick","funders":"","keywords":"Replica; Computer science; Sampling (signal processing); Hamiltonian (control theory); Statistical physics; Reaction coordinate; Basis (linear algebra); Sampling scheme; Umbrella sampling; Distributed computing; Theoretical computer science; Algorithm; Computational science; Molecular dynamics; Mathematical optimization; Physics; Mathematics; Computational chemistry; Detector; Geometry; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001981442,0.00004937997,0.00007453225,0.00001270542,0.00002026497,0.00001307536,0.00004210878,0.00005858688,0.000001282731],"category_scores_gemma":[0.00005889094,0.00004058125,0.00004175728,0.00002865329,0.00003474423,0.000003187607,0.00001979327,0.00006092124,1.547373e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000488775,"about_ca_system_score_gemma":0.00001246145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.625851e-7,"about_ca_topic_score_gemma":5.344912e-8,"domain_scores_codex":[0.9996238,0.00003079599,0.0001649682,0.00006813357,0.00005542454,0.00005691549],"domain_scores_gemma":[0.9997163,0.00002799236,0.0001192225,0.00004200368,0.00006745549,0.00002705271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002740213,0.00001844677,0.0001463902,0.000007078514,0.00001694989,0.000001838583,0.000005890173,0.0006282923,0.9853571,0.006109358,0.0001938121,0.007240837],"study_design_scores_gemma":[0.0007446355,0.0001681531,0.001185142,0.00002255958,0.00003390254,0.0003174485,0.00002285743,0.0005046299,0.5909132,0.4033533,0.002590598,0.0001435197],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7072785,0.0002940367,0.2922138,0.0000362841,0.00002417189,0.00001733493,0.000002868062,0.000001895851,0.0001310784],"genre_scores_gemma":[0.9964672,0.000009782328,0.003136558,0.000062439,0.0002637016,3.682795e-7,0.00004632561,0.000003864548,0.00000981684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3972439,"threshold_uncertainty_score":0.1654855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005778991128646618,"score_gpt":0.2542211554736589,"score_spread":0.2484421643450123,"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."}}