{"id":"W4404141186","doi":"10.3390/su16229698","title":"Effects of Land Use Data Spatial Resolution on SDG Indicator 11.3.1 (Urban Expansion) Assessments: A Case Study Across Ethiopia","year":2024,"lang":"en","type":"article","venue":"Sustainability","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Urban expansion; Geography; Land use; Environmental science; Environmental planning; Environmental resource management; Civil engineering; 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":[0.004652791,0.0004154365,0.000307419,0.0009723295,0.0008571126,0.001815996,0.0007208618,0.0004604821,0.001104127],"category_scores_gemma":[0.01119714,0.0002583313,0.0004672739,0.002693055,0.0007853201,0.00135704,0.001201888,0.0006675085,0.0002000757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001807392,"about_ca_system_score_gemma":0.0008927687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0348312,"about_ca_topic_score_gemma":0.03739285,"domain_scores_codex":[0.9971958,0.00150254,0.0001650203,0.0002956755,0.000559593,0.000281374],"domain_scores_gemma":[0.9890177,0.00751454,0.0008566301,0.000663812,0.001734426,0.0002128361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001543704,0.0009030495,0.6572652,0.0007517633,0.0004032654,0.00510088,0.007191154,0.180546,0.01188628,0.007471309,0.00394882,0.1229886],"study_design_scores_gemma":[0.0001613578,0.0012126,0.7056559,0.0005109829,0.0005467635,0.002449527,0.03859307,0.1791054,0.03615128,0.004982086,0.03032381,0.0003070577],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932648,0.0002338997,0.002005767,0.00018707,0.00001114591,0.00006212899,0.0006540799,0.00003970923,0.003541361],"genre_scores_gemma":[0.9941777,0.0002102255,0.004703468,0.00003758743,0.000005640203,0.00003940996,0.0003467205,0.00001753195,0.0004616928],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0348312,"threshold_uncertainty_score":0.0692569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01936631461920753,"score_gpt":0.3288154192728731,"score_spread":0.3094491046536655,"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."}}