{"id":"W1614714876","doi":"10.1063/1.1900405","title":"Chemical Master Equation Reduction Methods","year":2005,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Molecular Junctions and Nanostructures","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Master equation; Dimension (graph theory); Eigenvalues and eigenvectors; Computer science; Reduction (mathematics); Quadratic growth; Dimensionality reduction; Simple (philosophy); Applied mathematics; Invariant (physics); Chemical reaction; Matrix (chemical analysis); Mathematical optimization; Mathematics; Algorithm; Physics; Chemistry; Quantum mechanics; Artificial intelligence; Pure mathematics","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":[0.0008953524,0.0007914294,0.0007540786,0.001053252,0.0006049218,0.0009473343,0.001957578,0.001184415,0.01094599],"category_scores_gemma":[0.001905182,0.0003600331,0.001367075,0.0006313905,0.0008829172,0.001293106,0.001458083,0.002076215,0.002643709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008019881,"about_ca_system_score_gemma":0.0009286374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001225255,"about_ca_topic_score_gemma":0.001131431,"domain_scores_codex":[0.9994447,0.000183714,0.00001857242,0.00005631583,0.000253842,0.00004280909],"domain_scores_gemma":[0.9994791,0.0002203649,0.00004640926,0.0001031385,0.0001217643,0.00002920669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001216432,0.0000646971,0.0001645648,0.000156408,0.0000356943,0.00003928092,0.0001238053,0.07057026,0.003605349,0.8892912,0.004031062,0.03190557],"study_design_scores_gemma":[0.00002069472,0.00002708894,0.00008554319,0.00002291374,0.00001007125,0.00004836782,0.00002641083,0.6784918,0.001751191,0.3007245,0.01877044,0.00002111557],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007337554,0.0008163477,0.9569296,0.0007408225,0.0002548405,0.0001628918,0.0001960432,0.0003608653,0.0332009],"genre_scores_gemma":[0.199639,0.00216868,0.7441728,0.0006472301,0.0005036215,0.001077683,0.000600083,0.001022185,0.0501687],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01094599,"threshold_uncertainty_score":0.03661805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02962093971881879,"score_gpt":0.2668438339454753,"score_spread":0.2372228942266565,"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."}}