{"id":"W755741475","doi":"10.1371/journal.pone.0129606","title":"Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":193,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; Princess Margaret Cancer Centre; Hospital for Sick Children; University of Toronto; Public Health Ontario","funders":"Canadian Institutes of Health Research; Crohn's and Colitis Canada; Leona M. and Harry B. Helmsley Charitable Trust","keywords":"Akaike information criterion; Covariate; Model selection; Goodness of fit; Statistics; Count data; Type I and type II errors; Parametric statistics; Mathematics; Selection (genetic algorithm); Information Criteria; Likelihood-ratio test; Parametric model; Computer science; Econometrics; Artificial intelligence; Poisson distribution","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002236001,0.0000632211,0.0001232448,0.00002351259,0.0000341351,0.000008661648,0.00009587919,0.00007060973,0.000002057227],"category_scores_gemma":[0.000018093,0.00006436669,0.00001109433,0.00003824666,0.00002295247,0.000004762546,0.0001110939,0.00003753148,6.072086e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001262659,"about_ca_system_score_gemma":0.0001084113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002289657,"about_ca_topic_score_gemma":0.00001594899,"domain_scores_codex":[0.9994651,0.00002166869,0.0001410618,0.0002035067,0.0000476841,0.0001209529],"domain_scores_gemma":[0.9995618,0.000006541036,0.00007085848,0.0001696902,0.0001373977,0.0000536504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000333723,0.0001969821,0.00158504,0.00009468237,0.0000758146,5.360578e-8,0.00002319672,0.00001590092,0.9973698,0.00004316575,0.0004512166,0.0001108328],"study_design_scores_gemma":[0.002231801,0.0009088159,0.003286163,0.0001290122,0.0001560002,0.000008434888,0.00007958274,0.02583831,0.9654741,0.0002596923,0.0013719,0.0002561872],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943466,0.0002502188,0.004746271,0.0001010184,0.00001392402,0.0002527016,0.0001194492,0.00000575468,0.0001640923],"genre_scores_gemma":[0.9665055,0.00007552127,0.0325326,0.00005448237,0.00004810597,0.000005510441,0.000677113,0.00001087799,0.00009034635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03189564,"threshold_uncertainty_score":0.2624798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1219719700579063,"score_gpt":0.3207914810493371,"score_spread":0.1988195109914307,"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."}}