{"id":"W1974246826","doi":"10.1139/l03-051","title":"Identifying urban boundaries: application of remote sensing and geographic information system technologies","year":2003,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Urbanization; Multispectral image; Remote sensing; Geography; Geographic information system; Computer science; Urban agglomeration; Boundary (topology); Cartography; Satellite; Fuzzy logic; Data mining; Artificial intelligence; Mathematics; Engineering; Economic geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001532629,0.0004423382,0.0004663257,0.005141065,0.0004419747,0.00223629,0.0006777236,0.0007902582,0.00158327],"category_scores_gemma":[0.003782745,0.0002254763,0.0005056108,0.003249534,0.000962882,0.0020455,0.00111418,0.0004240032,0.0003278899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007441271,"about_ca_system_score_gemma":0.0006656332,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003911023,"about_ca_topic_score_gemma":0.003809968,"domain_scores_codex":[0.999032,0.0003633709,0.00006940672,0.0001277819,0.0003722586,0.00003514894],"domain_scores_gemma":[0.9987208,0.000761805,0.0001973876,0.00009925441,0.0001857525,0.00003501055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001029422,0.0001072454,0.02580073,0.000751993,0.0001602625,0.0007661032,0.00198047,0.08468942,0.006775861,0.0969889,0.002819928,0.7790562],"study_design_scores_gemma":[0.00006655965,0.0003100796,0.03363694,0.0008081971,0.0001789782,0.001934369,0.005551083,0.6401713,0.01562813,0.2381744,0.06333768,0.0002023415],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09076285,0.004399624,0.8702762,0.001645653,0.0001330214,0.000328953,0.0005499905,0.0009696505,0.03093403],"genre_scores_gemma":[0.4576832,0.00235777,0.5376053,0.0001706552,0.00007981652,0.0001614569,0.0004316149,0.00004103852,0.001469158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.996089,"threshold_uncertainty_score":0.008105397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003940001193664901,"score_gpt":0.1572211778975495,"score_spread":0.1532811767038846,"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."}}