{"id":"W1502399419","doi":"","title":"Minimum description length methods of medium-scale simultaneous inference","year":2010,"lang":"en","type":"article","venue":"","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Minimum description length; Inference; Feature selection; Bayes' theorem; Computer science; Statistic; Scale (ratio); Parametric statistics; Feature (linguistics); Selection (genetic algorithm); Algorithm; Data mining; Mathematics; Pattern recognition (psychology); Artificial intelligence; Statistics; Bayesian probability","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":[0.01903966,0.001287314,0.002021978,0.002728162,0.001288679,0.002712287,0.004556754,0.001929788,0.00517205],"category_scores_gemma":[0.06533541,0.001564879,0.002157738,0.002425488,0.003180418,0.004427691,0.005426915,0.005130009,0.001080439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00249011,"about_ca_system_score_gemma":0.002486329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003391633,"about_ca_topic_score_gemma":0.00312552,"domain_scores_codex":[0.9880694,0.007473806,0.0005428388,0.001383963,0.002127199,0.0004027354],"domain_scores_gemma":[0.9064756,0.08277815,0.002466849,0.004590269,0.002972985,0.0007161882],"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":[0.0004009994,0.0001558643,0.002370855,0.0004591976,0.0003741155,0.0002363356,0.000184965,0.5207123,0.001887594,0.3094888,0.003201493,0.1605275],"study_design_scores_gemma":[0.00001969467,0.00002797013,0.0001344716,0.00001938983,0.00001174416,0.00002070891,0.000008193308,0.8773276,0.0004231619,0.1214211,0.0005646159,0.0000214172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0020178,0.0001985863,0.997022,0.000177285,0.00001720439,0.0000313458,0.00007435902,0.0001256367,0.0003357808],"genre_scores_gemma":[0.1806339,0.0004967435,0.8123884,0.0003020791,0.0002985501,0.0007106694,0.001058393,0.0002617649,0.00384944],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01903966,"threshold_uncertainty_score":0.1006926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02256563470635057,"score_gpt":0.3472820784541248,"score_spread":0.3247164437477743,"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."}}