{"id":"W184316663","doi":"10.1007/bf03404950","title":"An Introduction to Multilevel Regression Models","year":2001,"lang":"en","type":"article","venue":"Canadian Journal of Public Health","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":147,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa; Institute for Clinical Evaluative Sciences; University of Toronto","funders":"Health Canada","keywords":"Multilevel model; Hierarchical database model; Computer science; Regression analysis; Regression; Statistical model; Data mining; Statistics; Artificial intelligence; Machine learning; Econometrics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.005405041,0.001573741,0.002088256,0.003225842,0.0008129291,0.002518072,0.002915758,0.003230086,0.01894129],"category_scores_gemma":[0.01941304,0.00172095,0.00329955,0.005779096,0.002348593,0.003459055,0.00237252,0.008827837,0.006784439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002003698,"about_ca_system_score_gemma":0.002618721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00611361,"about_ca_topic_score_gemma":0.00848157,"domain_scores_codex":[0.9959216,0.002449704,0.0003684873,0.0003793766,0.0007810403,0.0000996595],"domain_scores_gemma":[0.9868423,0.01104521,0.0003468644,0.0008331004,0.0007845587,0.0001479107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001194807,0.00004123518,0.000346992,0.0005303561,0.0001005077,0.0001146866,0.0002085001,0.007669989,0.0003431735,0.8683789,0.04183096,0.0804228],"study_design_scores_gemma":[0.00001066029,0.00001755188,0.0003890392,0.0002040335,0.00003835178,0.0001382169,0.00002809596,0.01643008,0.0001006568,0.8646823,0.1179181,0.00004300102],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003617462,0.02029475,0.9632912,0.006099845,0.001143184,0.00004796293,0.0006780194,0.0004220777,0.007661287],"genre_scores_gemma":[0.02221001,0.04429403,0.9018724,0.005343156,0.006708761,0.00090941,0.001165938,0.0007075964,0.0167887],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01894129,"threshold_uncertainty_score":0.06336492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2217328318533305,"score_gpt":0.4339817907005796,"score_spread":0.2122489588472491,"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."}}