{"id":"W3036120216","doi":"10.1002/cjs.11556","title":"Inference for misclassified multinomial data with covariates","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Covariate; Multinomial distribution; Inference; Bayesian probability; Computer science; Classifier (UML); Subject (documents); Multinomial logistic regression; Statistics; Bayesian inference; Artificial intelligence; Econometrics; Mathematics; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0003378385,0.0001421362,0.0003589209,0.00006090495,0.0001061292,0.0001052128,0.0005419023,0.00005801002,0.0002019407],"category_scores_gemma":[0.01286532,0.0001106636,0.00002347198,0.0001117317,0.0001495465,0.0001071994,0.0000223352,0.0002240923,0.000003983331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004125713,"about_ca_system_score_gemma":0.001817778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000301056,"about_ca_topic_score_gemma":0.003453639,"domain_scores_codex":[0.998841,0.0000629339,0.0004733701,0.0001717086,0.0001638084,0.0002871068],"domain_scores_gemma":[0.9951792,0.002933508,0.0003402265,0.0002339913,0.0004743563,0.0008387084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001531547,0.00001842013,0.001855577,0.0002017358,0.0001056863,0.0002440522,0.0006444357,0.00000576261,0.0000590266,0.9137471,0.05401983,0.02894524],"study_design_scores_gemma":[0.003105972,0.001689984,0.003667692,0.0002706585,0.0005135081,0.0001138444,0.0005406453,0.03242145,0.0001970437,0.9299105,0.02695116,0.000617488],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002792188,0.00002309988,0.9907201,0.0009898035,0.0001553521,0.0001598454,0.007461456,0.000005864734,0.0002052421],"genre_scores_gemma":[0.06194781,0.000003901253,0.9374034,0.0003298775,0.000234497,0.000001973626,0.00004227529,0.00002283757,0.00001346096],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06166859,"threshold_uncertainty_score":0.9954497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1936066752888718,"score_gpt":0.3686499324939307,"score_spread":0.1750432572050588,"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."}}