{"id":"W4235587499","doi":"10.1007/978-3-319-44677-6_29","title":"Off-Lattice Kinetic Monte Carlo Methods","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Catalytic Processes in Materials Science","field":"Materials Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; Regroupement Québécois sur les Matériaux de Pointe; Université de Montréal","funders":"","keywords":"Kinetic Monte Carlo; Statistical physics; Lattice (music); Monte Carlo method; Limiting; Discretization; Computer science; Physics; Mathematics; Engineering","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001151681,0.0006519902,0.0009342056,0.000129856,0.0001388345,0.0003788478,0.001767103,0.0003833238,0.0136313],"category_scores_gemma":[0.0005250995,0.0005728537,0.0001845613,0.00009122674,0.000560311,0.0002979361,0.001031911,0.000337915,0.006980511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001468602,"about_ca_system_score_gemma":0.0003082522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006918688,"about_ca_topic_score_gemma":0.00001672767,"domain_scores_codex":[0.9963422,0.00006686115,0.0008425571,0.001368707,0.0008425683,0.0005371187],"domain_scores_gemma":[0.9974445,0.0003489886,0.0004743512,0.001152058,0.000235104,0.000345036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000090081,0.00003066276,6.823564e-7,0.0007585636,0.00004862581,0.0002140147,0.0003761316,0.0001073751,0.6806921,0.2875593,0.01625658,0.01386588],"study_design_scores_gemma":[0.0003528334,0.0001921806,0.000004380226,0.0002895241,0.0002973945,0.00016001,0.00002911009,0.001217861,0.2270674,0.05764602,0.7111148,0.001628517],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000242927,0.001775158,0.008953968,0.00076107,0.003429702,0.0005479956,0.0001426603,0.0006256318,0.9835209],"genre_scores_gemma":[0.005520168,0.00028908,0.2084321,0.002296495,0.0009781511,0.00003523824,0.00001725855,0.0002056869,0.7822258],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6948582,"threshold_uncertainty_score":0.9996723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03876644165422309,"score_gpt":0.3165088696794757,"score_spread":0.2777424280252526,"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."}}