{"id":"W2475351935","doi":"","title":"Learning and Testing Junta Distributions","year":2016,"lang":"en","type":"article","venue":"Conference on Learning Theory","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Hypercube; Uniform distribution (continuous); Distribution (mathematics); Mathematics; Boolean function; Property testing; Domain (mathematical analysis); Combinatorics; Discrete mathematics; Set (abstract data type); Algorithm; Computer science; Statistics; Mathematical analysis","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":[],"consensus_categories":[],"category_scores_codex":[0.001005466,0.000187268,0.0001723677,0.0001000764,0.0005770712,0.000212932,0.0004271637,0.00006929474,0.0001068992],"category_scores_gemma":[0.002863462,0.0001304723,0.00003812685,0.0002404083,0.0001511892,0.0002350395,0.0002822755,0.000575199,0.0002284543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002929911,"about_ca_system_score_gemma":0.00006653871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006832454,"about_ca_topic_score_gemma":4.002559e-7,"domain_scores_codex":[0.9983093,0.0004588893,0.0001727397,0.0004950803,0.0001917956,0.0003722615],"domain_scores_gemma":[0.9979833,0.001370297,0.0001295059,0.0002636305,0.0001097772,0.0001434632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005909716,0.00001390124,0.005983036,0.000004635628,0.000007148381,0.000008051718,0.0002249384,0.00004571738,0.001786798,0.4179159,0.00002214906,0.5739818],"study_design_scores_gemma":[0.003976902,0.004356097,0.07113781,0.002452641,0.00006828224,0.000357962,0.001120269,0.3338037,0.004069071,0.444439,0.1309714,0.003246917],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05432954,0.00006510798,0.9112205,0.002320646,0.0002064458,0.00008345559,0.000001704793,0.0008906107,0.03088198],"genre_scores_gemma":[0.983311,0.00003726901,0.006369432,0.00005805353,0.00008843831,0.0000100486,0.000002184201,0.00001440145,0.0101092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9289814,"threshold_uncertainty_score":0.5320507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02196962589253052,"score_gpt":0.2657186468250975,"score_spread":0.243749020932567,"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."}}