{"id":"W42142495","doi":"10.1007/978-3-642-21596-4_31","title":"Multiple Classifier System for Urban Area’s Extraction from High Resolution Remote Sensing Imagery","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Classifier (UML); Computer science; Artificial intelligence; Particle swarm optimization; Pattern recognition (psychology); Land cover; Thematic map; Feature extraction; Machine learning; Geography; Land use; Engineering; Cartography","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":[0.0004667811,0.000628489,0.0009424799,0.001633062,0.0005719565,0.0007137416,0.0009838387,0.0008912928,0.003526584],"category_scores_gemma":[0.0005718921,0.0003166322,0.0006401959,0.001175264,0.0001239909,0.0008366311,0.0005777656,0.000566387,0.002723622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003764801,"about_ca_system_score_gemma":0.0004981378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003594344,"about_ca_topic_score_gemma":0.006502541,"domain_scores_codex":[0.9996355,0.00002213947,0.00002349257,0.0001234446,0.000141096,0.00005438791],"domain_scores_gemma":[0.9997111,0.00004684523,0.00001970572,0.00003385875,0.0001694008,0.00001917277],"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":[0.000233491,0.0001367604,0.002351732,0.0001270138,0.00007087488,0.0001683372,0.00006196999,0.004832003,0.09196081,0.0006692379,0.008111974,0.8912759],"study_design_scores_gemma":[0.00003861722,0.0002934454,0.02243013,0.00005654131,0.0002882602,0.000798995,0.0001808815,0.8246949,0.1258205,0.002093968,0.02320443,0.00009935535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08681829,0.002007946,0.8945733,0.0002191112,0.0005294341,0.0002123976,0.001373511,0.008428828,0.005837229],"genre_scores_gemma":[0.3719998,0.001294209,0.6053812,0.0002481011,0.000270884,0.0002782985,0.003541389,0.0002662734,0.01671983],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003594344,"threshold_uncertainty_score":0.01179767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03281128768504257,"score_gpt":0.2263856965722037,"score_spread":0.1935744088871612,"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."}}