{"id":"W3139009748","doi":"10.1109/lgrs.2021.3060960","title":"Building Instance Extraction Method Based on Improved Hybrid Task Cascade","year":2021,"lang":"en","type":"article","venue":"IEEE Geoscience and Remote Sensing Letters","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Computer science; Notation; Artificial intelligence; Task (project management); Minimum bounding box; Algorithm; Mathematics; Image (mathematics); Engineering; Arithmetic","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":[0.0005233929,0.001468753,0.001228747,0.001638684,0.0005185572,0.0008442059,0.001933022,0.0009102161,0.004728062],"category_scores_gemma":[0.001119327,0.0005410897,0.001327675,0.001257871,0.0002721697,0.001651889,0.001177788,0.0008887935,0.002059786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005385574,"about_ca_system_score_gemma":0.0008554135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006078444,"about_ca_topic_score_gemma":0.009405967,"domain_scores_codex":[0.9992902,0.00004936222,0.00004009203,0.0002559722,0.000256687,0.0001075036],"domain_scores_gemma":[0.99961,0.00008378474,0.00003164378,0.00009542765,0.0001444401,0.00003473097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002698094,0.0001585093,0.002769898,0.0001645541,0.0001347856,0.0003790537,0.00008500244,0.05125033,0.08573613,0.002802522,0.01098695,0.8452624],"study_design_scores_gemma":[0.00002020616,0.00006995245,0.002313412,0.000008199836,0.00005097062,0.0003474454,0.00003001939,0.9597198,0.0322098,0.001614042,0.003589141,0.00002701657],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0506336,0.0003437771,0.9377483,0.0001400239,0.00008948285,0.0002456541,0.0005647226,0.005990977,0.004243439],"genre_scores_gemma":[0.3678909,0.000320332,0.6188752,0.0002675309,0.00009667738,0.0003049192,0.003705426,0.0003993042,0.008139678],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006078444,"threshold_uncertainty_score":0.01581693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009669899646633373,"score_gpt":0.2610974013126638,"score_spread":0.2514275016660305,"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."}}