{"id":"W7030255779","doi":"","title":"Model Selection via Minimum Description Length","year":2011,"lang":"en","type":"dissertation","venue":"Library and Archives Canada (Government of Canada)","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Minimum description length; Model selection; Categorical variable; Bayesian information criterion; Context (archaeology); Lasso (programming language); Population; Selection (genetic algorithm); Bayesian probability; Statistical model","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00001727011,0.000284208,0.0003144765,0.00004829545,0.0001703728,0.00004615459,0.0004776403,0.00009113293,0.000009735958],"category_scores_gemma":[0.000001666881,0.0002840919,0.00004672657,0.000103605,0.00002025034,0.0007397772,0.00007939175,0.0002485824,2.231683e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008715318,"about_ca_system_score_gemma":0.002120451,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002227889,"about_ca_topic_score_gemma":0.04638913,"domain_scores_codex":[0.9976805,0.00008334862,0.0003314977,0.0004393834,0.001165028,0.0003002693],"domain_scores_gemma":[0.9991665,0.00005985028,0.0002784186,0.0002729176,0.000001419913,0.0002208565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004054634,0.00006005399,0.000339231,0.0004854472,0.0001373622,0.0000328201,0.000764185,0.00008884608,0.0552175,0.7194975,0.001735921,0.2212356],"study_design_scores_gemma":[0.0004623659,0.0001681695,0.005843977,0.0003145917,0.0000872271,0.00001855279,0.0004174456,0.6207911,0.2048551,0.1626468,0.003331389,0.001063311],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006450065,0.0003274185,0.7146323,0.0002942104,0.0006757803,0.000209796,0.00003520555,0.00002942307,0.2773458],"genre_scores_gemma":[0.6436525,0.0003008434,0.2693914,0.0008748515,0.0001032398,0.00002580227,0.00004686966,0.00005076687,0.08555369],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6372024,"threshold_uncertainty_score":0.9999611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007966905076340727,"score_gpt":0.1653063325828643,"score_spread":0.1573394275065236,"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."}}