{"id":"W1972423301","doi":"10.1023/b:land.0000030442.96122.ef","title":"Sensitivity of landscape pattern indices to input data characteristics on real landscapes: implications for their use in natural disturbance emulation","year":2004,"lang":"en","type":"article","venue":"Landscape Ecology","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":109,"is_retracted":false,"has_abstract":false,"ca_institutions":"Sault College; Ontario Forest Research Institute","funders":"","keywords":"Thematic map; Landscape ecology; Emulation; Disturbance (geology); Land cover; Spatial analysis; Sensitivity (control systems); Computer science; Cartography; Environmental resource management; Data mining; Land use; Geography; Remote sensing; Environmental science; Ecology; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003270263,0.0001501258,0.0002928555,0.00007191883,0.00008027646,0.0000275474,0.0002915594,0.0001069975,0.00005050436],"category_scores_gemma":[0.00006190201,0.0001146647,0.00003242681,0.0001882588,0.0000108928,0.0002760926,0.0002155785,0.00009536165,0.00004813699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005243069,"about_ca_system_score_gemma":0.00001501222,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007923658,"about_ca_topic_score_gemma":0.09936827,"domain_scores_codex":[0.9988374,0.00006546434,0.0003074251,0.0004212414,0.0000853742,0.0002831227],"domain_scores_gemma":[0.9988644,0.0003729651,0.0001712202,0.0005103676,0.00001549179,0.00006559525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007669946,0.0001247087,0.9947285,0.00002699026,0.00001253207,0.000002488635,0.0004332112,0.001986973,0.000429536,0.0000257978,0.0001874301,0.001965147],"study_design_scores_gemma":[0.000685002,0.0001244108,0.9907277,0.00002846366,0.00001187211,0.000005397467,0.00004769874,0.007592716,0.00009048708,0.0001057983,0.000434939,0.0001454942],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976487,0.000008891177,0.0002150659,0.0006695847,0.0002078613,0.0004252462,0.0006826071,0.00002595147,0.0001160681],"genre_scores_gemma":[0.9984293,0.00003293981,0.0001299927,0.0003270306,0.0000828445,0.0000436192,0.0009329601,0.00001371851,0.000007571328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0985759,"threshold_uncertainty_score":0.9170659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02029926796112466,"score_gpt":0.2532546698814917,"score_spread":0.232955401920367,"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."}}