{"id":"W2942481792","doi":"10.1111/biom.13384","title":"Poisson PCA: Poisson measurement error corrected PCA, with application to microbiome data","year":2020,"lang":"en","type":"article","venue":"Biometrics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Poisson distribution; Outlier; Principal component analysis; Poisson regression; Parametric statistics; Variance (accounting); Transformation (genetics); Latent variable","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01060532,0.00153397,0.001525093,0.002670099,0.001584582,0.0022058,0.002334785,0.001933851,0.002194144],"category_scores_gemma":[0.04110787,0.0009090218,0.002296778,0.004078851,0.001847859,0.002121051,0.002939298,0.003155338,0.001473488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001148445,"about_ca_system_score_gemma":0.002702928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006964189,"about_ca_topic_score_gemma":0.006264809,"domain_scores_codex":[0.993619,0.003454419,0.0002841776,0.001106511,0.001316413,0.0002195879],"domain_scores_gemma":[0.9863854,0.008355085,0.001187291,0.001861771,0.001894569,0.0003159511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003932714,0.0001714334,0.01150036,0.000745126,0.000569729,0.0006201637,0.0007470593,0.2851786,0.007946454,0.1237182,0.01566114,0.5527486],"study_design_scores_gemma":[0.00003577062,0.00008909223,0.003308944,0.00007031931,0.00004369687,0.0004455757,0.0001215791,0.8625989,0.003618855,0.1161475,0.01342567,0.00009415302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002697336,0.0005245827,0.9953305,0.0002854484,0.0001077436,0.00004960264,0.0001164342,0.000576395,0.00031206],"genre_scores_gemma":[0.05767638,0.001276623,0.9364968,0.0003511003,0.0003914977,0.0003844039,0.0006722838,0.0005345524,0.002216329],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01060532,"threshold_uncertainty_score":0.05608696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3398189776315755,"score_gpt":0.3932750149486975,"score_spread":0.05345603731712195,"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."}}