{"id":"W2262162781","doi":"10.5623/cig2015-305","title":"Exploring the decision tree method FOR MODELLING URBAN LAND USE CHANGE","year":2015,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Geospatial analysis; Land use; Decision tree; Land use, land-use change and forestry; Change detection; Process (computing); Cohen's kappa; Computer science; Land cover; Geography; Data mining; Machine learning; Remote sensing; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0005151865,0.00007668803,0.000101908,0.00001293487,0.0001138275,0.0000639279,0.0001802287,0.00002110221,0.00004665762],"category_scores_gemma":[0.00002670676,0.00004241526,0.0000363053,0.00008069826,0.000004676382,0.0005260459,0.00009422923,0.00003040305,0.0002571043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002920911,"about_ca_system_score_gemma":0.000002282814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008805821,"about_ca_topic_score_gemma":0.0008764664,"domain_scores_codex":[0.9993218,0.00003081073,0.0001323422,0.0001442468,0.0001796196,0.0001911619],"domain_scores_gemma":[0.9993873,0.0002511765,0.00003832575,0.0002331896,0.000006556223,0.00008341511],"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":[0.0004581551,0.0003265979,0.2017368,0.0002949524,0.0001449154,0.00002090279,0.0569586,0.3391541,0.0001898652,0.0007883393,0.01769531,0.3822315],"study_design_scores_gemma":[0.0003350249,0.00004512395,0.004611839,0.00004120656,0.00002664993,0.000003658778,0.0002129899,0.9690951,0.0001018182,0.002828939,0.02257942,0.0001182344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8917612,0.00003140752,0.1068741,0.0002574931,0.0001673001,0.0003055348,0.000005170811,0.00003096961,0.0005668434],"genre_scores_gemma":[0.9355911,0.00002030099,0.06366199,0.0002153021,0.000188006,0.0002439309,0.000005072736,0.00001492146,0.00005940102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.629941,"threshold_uncertainty_score":0.3304642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2600511667339954,"score_gpt":0.2876552891315791,"score_spread":0.02760412239758364,"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."}}