{"id":"W2606320812","doi":"10.1371/journal.pone.0175194","title":"Model selection with multiple regression on distance matrices leads to incorrect inferences","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Trent University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Akaike information criterion; Bayesian information criterion; Spurious relationship; Deviance information criterion; Sample size determination; Statistics; Model selection; Selection (genetic algorithm); Pairwise comparison; Information Criteria; Distance matrices in phylogeny; Mathematics; Bayesian probability; Rank (graph theory); Computer science; Bayesian inference; Artificial intelligence","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.07490136,0.002315614,0.002989664,0.002901161,0.001420682,0.002645733,0.002438983,0.001759088,0.001062706],"category_scores_gemma":[0.2375286,0.00114292,0.002221662,0.002487704,0.003217787,0.003105226,0.002189378,0.004983544,0.000457482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001428782,"about_ca_system_score_gemma":0.002374677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005057272,"about_ca_topic_score_gemma":0.008365464,"domain_scores_codex":[0.9270536,0.06153651,0.002396252,0.003788262,0.004675571,0.0005496867],"domain_scores_gemma":[0.7471141,0.2282076,0.007560458,0.01184214,0.004552571,0.0007231756],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009427569,0.0003219371,0.1023628,0.001682744,0.005044206,0.001970233,0.002742094,0.4354109,0.01326691,0.1229481,0.007882782,0.3054246],"study_design_scores_gemma":[0.0001187826,0.0001812401,0.01090726,0.0002277048,0.000294583,0.0005840507,0.0003490114,0.7195923,0.00562597,0.2593574,0.002599327,0.0001624119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0774184,0.0007649888,0.9181692,0.001587912,0.0001305962,0.00008720085,0.0001324852,0.0007071785,0.001002122],"genre_scores_gemma":[0.6081091,0.0006337989,0.3882317,0.001463894,0.00009404054,0.0002606765,0.0002554454,0.0003943943,0.0005569712],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9250987,"threshold_uncertainty_score":0.396121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03613082544822418,"score_gpt":0.256132781770364,"score_spread":0.2200019563221398,"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."}}