{"id":"W2068337399","doi":"10.1007/s00267-010-9510-6","title":"Regionalization of Landscape Pattern Indices Using Multivariate Cluster Analysis","year":2010,"lang":"en","type":"article","venue":"Environmental Management","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":85,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Sport Centre Pacific; Natural Resources Canada; Canadian Forest Service; University of Victoria","funders":"","keywords":"Geography; Common spatial pattern; Forest management; Spatial ecology; Land cover; Land use; Multivariate statistics; Cartography; Ecology; Physical geography; Forestry; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001580941,0.0003965786,0.0005793891,0.003709524,0.0005129742,0.001127894,0.0004605392,0.0001508061,0.001834601],"category_scores_gemma":[0.004429135,0.0002092473,0.0007553289,0.003193424,0.0002418802,0.000493894,0.0006676487,0.0004393422,0.0003517002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005972005,"about_ca_system_score_gemma":0.0008166411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02030801,"about_ca_topic_score_gemma":0.02049914,"domain_scores_codex":[0.9993869,0.0001403346,0.00005484539,0.0001804076,0.0001526367,0.00008490174],"domain_scores_gemma":[0.9977278,0.0005383209,0.0002324938,0.0003883466,0.001004717,0.0001083868],"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":[0.001530546,0.0003931485,0.3779123,0.0002066455,0.0008962268,0.0001711765,0.001717971,0.03407334,0.0645843,0.003847802,0.004167283,0.5104992],"study_design_scores_gemma":[0.00007356852,0.0002520999,0.7848541,0.00002741985,0.0004113354,0.0002328465,0.001103405,0.1939991,0.01217675,0.002772059,0.003992907,0.0001044256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8699831,0.0001530123,0.1227318,0.00006009965,0.00002390923,0.0002329634,0.001848394,0.001115831,0.003850763],"genre_scores_gemma":[0.9133833,0.00005108675,0.08359547,0.000005904158,0.00001012408,0.0001511279,0.001770148,0.0002353231,0.0007974266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02030801,"threshold_uncertainty_score":0.04037964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006396906239092153,"score_gpt":0.2056872635127795,"score_spread":0.1992903572736874,"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."}}