{"id":"W2981846308","doi":"10.4095/219782","title":"Sensitivity of Landscape Indices to Classification Accuracy","year":2001,"lang":"en","type":"report","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Sensitivity (control systems); Computer science; Geography; Statistics; Cartography; Artificial intelligence; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02483514,0.000610231,0.000863368,0.001875876,0.000490322,0.002358824,0.000596848,0.001169018,0.001073807],"category_scores_gemma":[0.1516959,0.0005468071,0.0008626609,0.002251497,0.0012487,0.001945937,0.001318105,0.001307887,0.0003422248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001608148,"about_ca_system_score_gemma":0.0004425993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004746912,"about_ca_topic_score_gemma":0.002966275,"domain_scores_codex":[0.9769908,0.01218294,0.001146831,0.002763808,0.006074931,0.0008407615],"domain_scores_gemma":[0.7148618,0.2506773,0.008726045,0.01678475,0.008303501,0.0006465499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00123752,0.0001588832,0.2439123,0.0001609696,0.0006313033,0.0003258588,0.0003604975,0.6817085,0.01106766,0.00300959,0.001572837,0.05585408],"study_design_scores_gemma":[0.00004995353,0.0005002297,0.2194885,0.00007043777,0.0003020645,0.0008220256,0.0002102601,0.7410363,0.02635639,0.009073059,0.001917734,0.000173013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9347062,0.0009917745,0.05564578,0.0003824388,0.00006644704,0.0001554824,0.001140523,0.000614297,0.006297118],"genre_scores_gemma":[0.9889793,0.0001360813,0.009188419,0.0000972314,0.00002280329,0.00005077727,0.0008995999,0.0001573142,0.0004684752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02483514,"threshold_uncertainty_score":0.1313424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05816205347329144,"score_gpt":0.2889128933335078,"score_spread":0.2307508398602163,"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."}}