{"id":"W2560136348","doi":"10.1111/ecog.02881","title":"Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure","year":2016,"lang":"en","type":"article","venue":"Ecography","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":2439,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Overfitting; Random forest; Computer science; Cross-validation; Econometrics; Autoregressive model; Contrast (vision); Extrapolation; Data mining; Ecology; Statistics; Machine learning; Mathematics; Artificial intelligence; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04089433553728782,"score_gpt":0.2890296900713945,"score_spread":0.2481353545341066,"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."}}