{"id":"W2164319128","doi":"","title":"Learning with Tree-Averaged Densities and Distributions","year":2007,"lang":"en","type":"article","venue":"","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Tree (set theory); Categorical variable; Multivariate statistics; Computer science; Mathematics; Joint probability distribution; Algorithm; Applied mathematics; Statistics; Data mining; Combinatorics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001623754,0.00004095512,0.00004898021,0.00001111368,0.0001878993,0.000007713807,0.00002405795,0.00002543063,0.001321372],"category_scores_gemma":[0.000009902457,0.0000289597,0.00001115995,0.00009875928,0.0001594746,0.00006741432,0.00002873686,0.00007056993,0.0001047672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001648479,"about_ca_system_score_gemma":0.000001146799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002212157,"about_ca_topic_score_gemma":0.002968288,"domain_scores_codex":[0.9996614,0.00001501015,0.00004749123,0.00009662523,0.00006001562,0.0001194604],"domain_scores_gemma":[0.9998569,0.0000393539,0.00001230887,0.00004700428,0.0000016296,0.00004272517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001962479,0.00001437109,0.9924395,5.129447e-7,0.00001586068,0.00002294927,0.0003342887,0.0005955209,0.001129263,0.0004566672,0.0002388822,0.004732542],"study_design_scores_gemma":[0.0002498443,0.0001144296,0.9853058,0.000001514282,0.00004459197,0.00003786575,0.0005763954,0.004578753,0.001946723,0.0003988703,0.006605103,0.0001401117],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9271114,0.000004982046,0.02550623,0.0001473811,0.00000380052,0.00001557539,2.398465e-7,0.00002574311,0.04718463],"genre_scores_gemma":[0.9931704,0.000003262814,0.0009491062,0.00008859019,0.0000063394,5.841413e-7,0.000004033539,0.000001779102,0.005775898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06605899,"threshold_uncertainty_score":0.9995915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003705070253384853,"score_gpt":0.1940986372829134,"score_spread":0.1903935670295286,"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."}}