{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01422162,0.001948748,0.003474217,0.003787132,0.001279211,0.002894855,0.003521676,0.002239519,0.005351656],"category_scores_gemma":[0.04338635,0.001474474,0.00270526,0.003170308,0.00152675,0.002697417,0.004136381,0.004436224,0.001487309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00196509,"about_ca_system_score_gemma":0.004034031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004094969,"about_ca_topic_score_gemma":0.003854007,"domain_scores_codex":[0.987644,0.009068554,0.0004923289,0.0009757856,0.001515755,0.0003035653],"domain_scores_gemma":[0.9685652,0.02684136,0.001182045,0.001253695,0.001781053,0.0003766122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002066222,0.0001428845,0.002484717,0.0005933344,0.0007447504,0.0003399206,0.0002258782,0.6669604,0.001010468,0.1069531,0.008947137,0.2113908],"study_design_scores_gemma":[0.0000392624,0.0000550969,0.0001953118,0.00005126622,0.00004186119,0.0000384411,0.00001950954,0.9296262,0.0003705701,0.06804844,0.001486805,0.00002728965],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001982228,0.000444432,0.9963384,0.0002955213,0.00002660815,0.00007982344,0.0001406766,0.0002173042,0.0004750905],"genre_scores_gemma":[0.1350025,0.001689759,0.8540872,0.0007106516,0.0003039685,0.001752728,0.002805502,0.000493493,0.003154135],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01422162,"threshold_uncertainty_score":0.07521206,"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."}}