{"id":"W7017481316","doi":"","title":"Bayesian Quantile Regression Based on the Generalized Gamma Distribution","year":2021,"lang":"en","type":"article","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Windsor","keywords":"Quantile regression; Akaike information criterion; Quantile; Deviance (statistics); Deviance information criterion; Bayesian probability; Bayesian information criterion; Bayesian linear regression; Gamma distribution; Bayes estimator","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.01228327,0.0009909482,0.00189385,0.002361841,0.0005743793,0.00211614,0.002328263,0.001423697,0.004010392],"category_scores_gemma":[0.03360606,0.0006649167,0.001720523,0.003122994,0.001598995,0.002239234,0.001780125,0.002409231,0.001104098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001506151,"about_ca_system_score_gemma":0.001678622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008488133,"about_ca_topic_score_gemma":0.005248317,"domain_scores_codex":[0.9941819,0.003774903,0.0001755052,0.0007935531,0.0007733083,0.0003008081],"domain_scores_gemma":[0.9872751,0.009828878,0.00092083,0.0008843594,0.0009558257,0.000135072],"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":[0.0002162316,0.00007664146,0.009966827,0.0002637798,0.0002943719,0.0002636893,0.0003580609,0.6309931,0.002403383,0.187363,0.003620397,0.1641804],"study_design_scores_gemma":[0.00002533882,0.00004568789,0.002475752,0.00006061679,0.00004435538,0.0001113974,0.00005061004,0.8968858,0.0006014117,0.09702228,0.002633195,0.00004364977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005876402,0.0003311792,0.9925489,0.0001593001,0.00001737306,0.00003912456,0.0001124774,0.000270258,0.0006449341],"genre_scores_gemma":[0.5121278,0.002642947,0.4765336,0.0003922622,0.0001647248,0.0005304006,0.001168751,0.0004419065,0.005997595],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01228327,"threshold_uncertainty_score":0.06496096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115514314588116,"score_gpt":0.244297007037776,"score_spread":0.2231418638918948,"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."}}