{"id":"W4210335523","doi":"10.1080/17538947.2021.2017035","title":"An efficient built-up land expansion model using a modified U-Net","year":2022,"lang":"en","type":"article","venue":"International Journal of Digital Earth","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Cellular automaton; Metric (unit); Urban expansion; Computer science; Random forest; Baseline (sea); Net (polyhedron); Land use; Urbanization; Environmental science; Remote sensing; Algorithm; Geography; Mathematics; Artificial intelligence; Civil engineering; Engineering; Geometry; Geology","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":[0.0002938168,0.0005530155,0.0005415874,0.000492355,0.0003791394,0.000580447,0.00158183,0.0008759625,0.001657824],"category_scores_gemma":[0.0005593315,0.0003909939,0.0006708286,0.0004984451,0.0004172802,0.0009000349,0.0005940271,0.0005080989,0.0002068506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001142218,"about_ca_system_score_gemma":0.001063071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05238906,"about_ca_topic_score_gemma":0.03823549,"domain_scores_codex":[0.9998741,0.00001703857,0.000007355496,0.00004720521,0.0000225799,0.00003168773],"domain_scores_gemma":[0.9998559,0.00005115156,0.00001765939,0.00001218484,0.00004817652,0.00001491742],"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":[0.0000194842,0.0000132892,0.000827983,0.000007119141,0.00001114889,0.00002920535,0.000007305196,0.9891782,0.0004823156,0.0007789783,0.0001813141,0.008463733],"study_design_scores_gemma":[8.745741e-7,0.000002482282,0.00007107281,6.475562e-7,0.000001512524,0.000002361544,9.033089e-7,0.9996481,0.00009303031,0.0001311247,0.00004702364,8.631485e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2348004,0.0004285271,0.7534576,0.0002933088,0.0001252031,0.00008910903,0.000526129,0.001761656,0.008518033],"genre_scores_gemma":[0.9365197,0.0001314923,0.05870201,0.00009559657,0.00001912196,0.00009776955,0.000352578,0.00005013344,0.004031479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05238906,"threshold_uncertainty_score":0.1041682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02208267526217657,"score_gpt":0.2558112205785329,"score_spread":0.2337285453163564,"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."}}