{"id":"W4386134063","doi":"10.1080/01621459.2023.2250098","title":"Spectral Clustering, Bayesian Spanning Forest, and Forest Process","year":2023,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Pfizer; Novartis Pharmaceuticals Corporation; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Eisai; National Institute on Aging; Alzheimer's Association","keywords":"Cluster analysis; Bayesian probability; Environmental science; Forestry; Mathematics; Statistics; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009628969,0.00009235791,0.00024798,0.00008391087,0.0001195887,0.0001327871,0.0003758486,0.00002734299,0.00000165235],"category_scores_gemma":[0.000936088,0.00006258216,0.00006335769,0.0005194022,0.00005751153,0.0002244954,0.0001107821,0.0002424948,0.000002490003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001193774,"about_ca_system_score_gemma":0.00007246349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000211625,"about_ca_topic_score_gemma":0.00002879024,"domain_scores_codex":[0.9986706,0.0001964364,0.0003057711,0.000132709,0.0004363935,0.000258026],"domain_scores_gemma":[0.9983001,0.0005885115,0.0007584749,0.0001284665,0.0001204574,0.0001039542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001071744,0.0001228675,0.5483466,0.00009113207,0.0002857818,0.0001564964,0.003573392,0.003421571,0.0006104187,0.128604,0.01563404,0.2990465],"study_design_scores_gemma":[0.0002267268,0.0001860857,0.5879689,0.00003447762,0.00003000401,0.00005032486,0.00004966079,0.267184,0.00002142492,0.1439697,0.0001687308,0.0001098953],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07732817,0.00001157502,0.9188895,0.003330561,0.0002185222,0.00005711364,0.000004827804,0.00002504162,0.0001346768],"genre_scores_gemma":[0.7851144,0.00001727393,0.2142483,0.0003044668,0.0001589659,0.000001573285,4.537801e-7,0.000008214076,0.0001463736],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7077863,"threshold_uncertainty_score":0.2552026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01116288481684367,"score_gpt":0.2962793568059756,"score_spread":0.2851164719891319,"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."}}