{"id":"W4406998231","doi":"10.1016/j.rsase.2025.101464","title":"Analysis of asbestos-cement roof classification in urban areas: Supervised and unsupervised methods with multispectral and hyperspectral remote sensing","year":2025,"lang":"en","type":"article","venue":"Remote Sensing Applications Society and Environment","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Public Health","funders":"European Space Agency; Universidad de Granada; Ryerson University; Universidad de Cartagena; Sistema General de Regalías de Colombia; Toronto Metropolitan University","keywords":"Multispectral image; Hyperspectral imaging; Asbestos cement; Asbestos; Remote sensing; Multispectral pattern recognition; Environmental science; Artificial intelligence; Cartography; Computer science; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000991111,0.000565822,0.0003282364,0.002151485,0.0002430692,0.0006198939,0.0003801075,0.0003724798,0.0003658665],"category_scores_gemma":[0.001156298,0.0001163943,0.0006796858,0.001155732,0.0003395974,0.0004617434,0.0003853293,0.0002363613,0.0002634136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002345438,"about_ca_system_score_gemma":0.0003710003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002727721,"about_ca_topic_score_gemma":0.005576754,"domain_scores_codex":[0.9992515,0.0001580435,0.00004881126,0.0001557987,0.0003290121,0.00005671343],"domain_scores_gemma":[0.9991756,0.0002631531,0.0001686704,0.00007394572,0.0002880622,0.00003054872],"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":[0.0003864376,0.0007169866,0.1048553,0.0005377408,0.0004213022,0.0002901414,0.0007499702,0.0824613,0.09944412,0.001069405,0.001693953,0.7073734],"study_design_scores_gemma":[0.00001920671,0.0002397884,0.2291266,0.00005924947,0.0001491204,0.0003645112,0.0009164191,0.7126583,0.0525039,0.001034731,0.002862547,0.00006569573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7446049,0.0004827032,0.2510735,0.00007153811,0.00002923666,0.000123803,0.0003873383,0.0005226301,0.002704372],"genre_scores_gemma":[0.8829311,0.0002423425,0.1144456,0.00002373789,0.00001930225,0.00008506884,0.000823697,0.00005354403,0.0013757],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002727721,"threshold_uncertainty_score":0.005423725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01478453725813527,"score_gpt":0.2530137882383608,"score_spread":0.2382292509802256,"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."}}