{"id":"W1846739556","doi":"10.5623/cig2011-061","title":"Second Generation Curvelet Transform for Building Extraction from High Resolution Satellite Imagery","year":2011,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Curvelet; Panchromatic film; Computer science; Multispectral image; Artificial intelligence; Computer vision; Remote sensing; Radon transform; Satellite imagery; Image fusion; Satellite; Image resolution; Pattern recognition (psychology); Wavelet transform; Geography; Image (mathematics); Wavelet; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001833785,0.0001641957,0.0001613779,0.0001034616,0.000130683,0.00004953725,0.00007272849,0.0001562049,0.0004152196],"category_scores_gemma":[0.00001826882,0.000169179,0.00007437301,0.00009877139,0.00001634174,0.0005629675,0.000004920255,0.0001245415,0.00005460717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009162464,"about_ca_system_score_gemma":0.000009772812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005952626,"about_ca_topic_score_gemma":0.00005331585,"domain_scores_codex":[0.9990858,0.00001792315,0.0003269312,0.0001948716,0.0001145616,0.0002599291],"domain_scores_gemma":[0.999616,0.00005864519,0.00006043936,0.0001697089,0.00003996933,0.00005528979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004439429,0.00007138629,0.00003676405,0.0001925444,0.0001179524,0.000004908238,0.0008991975,0.002175479,0.850309,0.001233426,0.003999235,0.1409158],"study_design_scores_gemma":[0.0007234081,0.00007977645,0.01983162,0.00009280886,0.0001205259,0.00001978069,0.00007671672,0.3262315,0.6272078,0.008052081,0.01701874,0.0005452073],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6413287,0.0002341227,0.3543305,0.00003229785,0.0009553521,0.0003008095,0.0000601116,0.0006601553,0.002097939],"genre_scores_gemma":[0.939952,0.00009595255,0.05910873,0.00001987812,0.0004152989,0.00007191421,0.0002107906,0.00004372676,0.00008175559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3240561,"threshold_uncertainty_score":0.6898919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02624322658682431,"score_gpt":0.2313624845141421,"score_spread":0.2051192579273178,"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."}}