{"id":"W4253314280","doi":"10.22215/etd/2018-13324","title":"Comparison of Finite and Infinite Mixture Models for Capturing Compositional Heterogeneity Across Sites","year":2018,"lang":"en","type":"dissertation","venue":"","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Bayesian probability; Set (abstract data type); Discretization; Gamma distribution; Mixture model; Sequence (biology); Range (aeronautics); Computer science; Finite set; Mathematics; Statistics; Engineering; Biology","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":[0.02318333,0.001437193,0.00177874,0.00317479,0.0009964994,0.002381708,0.003390283,0.002517512,0.001169079],"category_scores_gemma":[0.04833073,0.0007961399,0.002692343,0.001688813,0.001317714,0.005084416,0.002004442,0.003388951,0.0005168112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001775012,"about_ca_system_score_gemma":0.001670979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01567136,"about_ca_topic_score_gemma":0.01363146,"domain_scores_codex":[0.9931341,0.004924282,0.0003153032,0.0007491034,0.000665647,0.0002115611],"domain_scores_gemma":[0.964022,0.03073604,0.001253092,0.001677674,0.001845167,0.0004660636],"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":[0.0004358958,0.0001614286,0.008436944,0.0001554905,0.0003603249,0.0000759023,0.0005072934,0.9329897,0.001707453,0.01667377,0.0005155475,0.03798036],"study_design_scores_gemma":[0.00001912446,0.00004851077,0.001204718,0.00002724908,0.00003627565,0.00002362488,0.00005613454,0.9876201,0.0004083042,0.01019428,0.0003240085,0.00003773719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1836733,0.001324413,0.8119724,0.0004025124,0.00007891309,0.000171052,0.0002289925,0.0007579801,0.00139044],"genre_scores_gemma":[0.6851081,0.0006075813,0.3110782,0.0002184077,0.00004359132,0.0004261725,0.001294047,0.0002779893,0.0009458183],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02318333,"threshold_uncertainty_score":0.1226066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06288461543494439,"score_gpt":0.3417694336047771,"score_spread":0.2788848181698327,"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."}}