{"id":"W2144819008","doi":"10.1139/x02-011","title":"Predictive mapping of forest composition and structure with direct gradient analysis and nearest- neighbor imputation in coastal Oregon, U.S.A.","year":2002,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":544,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Forest Service; Oregon State University","keywords":"Thematic Mapper; Gradient analysis; Vegetation (pathology); k-nearest neighbors algorithm; Imputation (statistics); Geography; Vegetation classification; Environmental science; Remote sensing; Physical geography; Satellite imagery; Missing data; Statistics; Ordination; Mathematics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267642147262731,"score_gpt":0.2288029260514897,"score_spread":0.2161265045788624,"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."}}