{"id":"W1999583826","doi":"10.1109/isspa.2012.6310623","title":"Object- versus pixel-based building detection for disaster response","year":2012,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Pixel; Computer science; Object (grammar); Disaster response; Object detection; Field (mathematics); Artificial intelligence; Computer vision; Emergency management; Data mining; Pattern recognition (psychology); Mathematics","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":[0.0009131234,0.0003990847,0.0005602762,0.001650173,0.0002581061,0.0007735161,0.0004947343,0.0009136217,0.001857805],"category_scores_gemma":[0.001307752,0.0001958529,0.0003399204,0.00082641,0.0003852138,0.0008670349,0.0004402671,0.0002748891,0.0007162265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002581533,"about_ca_system_score_gemma":0.0002247491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009169827,"about_ca_topic_score_gemma":0.00155376,"domain_scores_codex":[0.999454,0.0001687182,0.00001773613,0.00008086108,0.0002235241,0.00005523373],"domain_scores_gemma":[0.9995818,0.0001589904,0.00003169124,0.00006102364,0.0001354853,0.00003109266],"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":[0.0009800062,0.0003574406,0.01236761,0.0002615533,0.0001816295,0.0001411565,0.0001263867,0.03746076,0.1275705,0.005363376,0.002850836,0.8123388],"study_design_scores_gemma":[0.00007175412,0.000597227,0.03031823,0.00004327044,0.0001968373,0.0005796034,0.0002020879,0.8829395,0.06953294,0.005461963,0.009979998,0.00007657791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2689613,0.002316695,0.7163627,0.0004698847,0.0003280552,0.0001320555,0.0001771848,0.002432302,0.00881994],"genre_scores_gemma":[0.6502489,0.0005810547,0.3465234,0.0001291064,0.0001131114,0.00004646006,0.0001961691,0.0001176985,0.00204411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001857805,"threshold_uncertainty_score":0.006215036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03111455700406378,"score_gpt":0.2700078076759522,"score_spread":0.2388932506718884,"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."}}