{"id":"W2150081678","doi":"10.1002/cphc.200400669","title":"Blue Moon Sampling, Vectorial Reaction Coordinates, and Unbiased Constrained Dynamics","year":2005,"lang":"en","type":"article","venue":"ChemPhysChem","topic":"Advanced Thermodynamics and Statistical Mechanics","field":"Physics and Astronomy","cited_by":185,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Scalar (mathematics); Reaction coordinate; Sampling (signal processing); Dynamics (music); Molecular dynamics; Conditional expectation; Stochastic dynamics; Perspective (graphical); Statistical physics; Mathematics; Physics; Chemistry; Computational chemistry; Statistics; Geometry; Optics","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":[0.001183007,0.000502494,0.0006796375,0.0008563718,0.000492393,0.0009350236,0.001028974,0.0009388488,0.003398894],"category_scores_gemma":[0.006345379,0.0003555976,0.0004688422,0.0007458072,0.001446282,0.002183651,0.001626781,0.0009150137,0.0004215349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000648228,"about_ca_system_score_gemma":0.000531078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001871025,"about_ca_topic_score_gemma":0.001660225,"domain_scores_codex":[0.9993699,0.0002322685,0.0000217596,0.00009378151,0.0002140027,0.00006833574],"domain_scores_gemma":[0.9989836,0.0005498309,0.0001342393,0.000161685,0.000110842,0.00005976197],"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":[0.00004401715,0.0000203591,0.0004907792,0.00006138934,0.00002099487,0.00009154578,0.00006695167,0.09614632,0.002989274,0.875491,0.001676693,0.02290076],"study_design_scores_gemma":[0.00001319381,0.00002457485,0.0003027698,0.0000140594,0.000006866251,0.00005823504,0.00001354363,0.6856716,0.001852256,0.308634,0.003380212,0.00002879947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02484681,0.0007811469,0.966935,0.0005219033,0.0001539644,0.00002574211,0.00009384912,0.0001886369,0.006452956],"genre_scores_gemma":[0.6399186,0.001786986,0.3443207,0.0007140366,0.0003363114,0.0002839587,0.0003423638,0.0006485274,0.01164853],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003398894,"threshold_uncertainty_score":0.01137042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118949448776242,"score_gpt":0.2563375481028118,"score_spread":0.2451480536150494,"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."}}