{"id":"W2328173450","doi":"10.1080/02533839.2008.9671417","title":"Distance weighted multiple classifiers systems applied to remote sensing images classification/data fusion","year":2008,"lang":"en","type":"article","venue":"Journal of the Chinese Institute of Engineers","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Council; Jet Propulsion Laboratory; Temple University; Ryerson University","keywords":"Boosting (machine learning); Weighting; Pattern recognition (psychology); Artificial intelligence; Random subspace method; Classifier (UML); Computer science; Fusion; Fuse (electrical); Data mining; Sensor fusion; Machine learning; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.004093322,0.0007326695,0.001509233,0.001771801,0.0006677051,0.001546267,0.001157408,0.001227642,0.001341934],"category_scores_gemma":[0.007165573,0.000429086,0.0007084328,0.001404232,0.0005699598,0.001599898,0.001052596,0.001028118,0.0006626576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008757831,"about_ca_system_score_gemma":0.0006916638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00185016,"about_ca_topic_score_gemma":0.001114283,"domain_scores_codex":[0.9963362,0.001134765,0.0004039019,0.0006027666,0.001365196,0.0001570776],"domain_scores_gemma":[0.9968381,0.001012331,0.000296987,0.0003208116,0.001454952,0.00007675907],"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":[0.0003812739,0.0001806763,0.002257533,0.0002433845,0.0003648112,0.000189726,0.0001823356,0.295635,0.02511215,0.01043519,0.001360371,0.6636577],"study_design_scores_gemma":[0.00001257308,0.0001302187,0.0006068341,0.000015741,0.000056797,0.00007230124,0.00002089267,0.9850005,0.008592473,0.004104996,0.001366857,0.00001981812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04108,0.001289497,0.9552901,0.0001950887,0.0002070882,0.0001106385,0.00002181643,0.0004437089,0.00136204],"genre_scores_gemma":[0.7014683,0.0005685706,0.2952504,0.0001195167,0.0001987769,0.0001386878,0.00006726097,0.00003851272,0.00214994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004093322,"threshold_uncertainty_score":0.02164781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02618824628705484,"score_gpt":0.2373709949244846,"score_spread":0.2111827486374298,"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."}}