{"id":"W2006722621","doi":"10.1007/s10910-011-9818-3","title":"Finding minimum energy reaction paths on ab initio potential energy surfaces using the fast marching method","year":2011,"lang":"en","type":"article","venue":"Journal of Mathematical Chemistry","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Fast marching method; Isomerization; Ab initio; Energy (signal processing); Gaussian; Mathematical chemistry; Potential energy; Energy profile; Chemistry; Mass spectrometry; Ab initio quantum chemistry methods; Reaction mechanism; Computational chemistry; Physical chemistry; Algorithm; Mathematics; Physics; Atomic physics; Catalysis; Quantum mechanics; Organic chemistry","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":[0.001004911,0.000918128,0.001117315,0.0009707716,0.0008631398,0.001030642,0.001394512,0.001852542,0.003904838],"category_scores_gemma":[0.0035296,0.001074027,0.0009767537,0.0007934698,0.0009419086,0.001234024,0.0009337469,0.001547985,0.0005251462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009589033,"about_ca_system_score_gemma":0.001842749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006642018,"about_ca_topic_score_gemma":0.005709601,"domain_scores_codex":[0.9997233,0.000113857,0.00001194416,0.00003069183,0.00008413054,0.00003612179],"domain_scores_gemma":[0.9986516,0.001049969,0.00006880151,0.00008047388,0.0001102612,0.00003892728],"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":[0.00006490474,0.00003560413,0.0003185666,0.00009068807,0.00002630838,0.00007479465,0.00005382584,0.9599339,0.001178114,0.02129724,0.0005074592,0.01641855],"study_design_scores_gemma":[0.00001347375,0.000006546565,0.00002451909,0.000004159762,0.000002080158,0.000004506202,0.0000045212,0.9922644,0.000273853,0.007216742,0.000181999,0.000003162965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09554128,0.0004303814,0.8959076,0.0004041762,0.00008625098,0.0001797412,0.0002032602,0.0008533231,0.006393948],"genre_scores_gemma":[0.4160626,0.0003298304,0.577987,0.0000931836,0.00002814469,0.000579469,0.0002673084,0.0004236535,0.004228898],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006642018,"threshold_uncertainty_score":0.01320672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03987870531986855,"score_gpt":0.2966508623178707,"score_spread":0.2567721569980022,"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."}}