{"id":"W4387925072","doi":"10.1016/j.jag.2023.103522","title":"Building and road detection from remote sensing images based on weights adaptive multi-teacher collaborative distillation using a fused knowledge","year":2023,"lang":"en","type":"article","venue":"International Journal of Applied Earth Observation and Geoinformation","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Science Foundation of Fujian Province; National Natural Science Foundation of China","keywords":"Distillation; Robustness (evolution); Computer science; Machine learning; Artificial intelligence; Feature (linguistics); Transfer of learning; Ensemble learning; Pattern recognition (psychology); Data mining; Chemistry; Chromatography","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":[0.000495781,0.001392875,0.001012851,0.001216834,0.0004625097,0.0007285036,0.001709378,0.001002838,0.001289053],"category_scores_gemma":[0.00142396,0.000462615,0.001071144,0.0009982769,0.0005094934,0.002481,0.001553068,0.00173962,0.0007999753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005083496,"about_ca_system_score_gemma":0.0009344216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008486856,"about_ca_topic_score_gemma":0.01500723,"domain_scores_codex":[0.9995078,0.00005739207,0.00002036878,0.0002215642,0.000109059,0.00008387059],"domain_scores_gemma":[0.9996648,0.00008268579,0.00003557703,0.00009842301,0.00009324805,0.00002530145],"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":[0.0002697367,0.0002275192,0.002747461,0.0001741857,0.000150315,0.0001982713,0.0002191554,0.2159245,0.03029977,0.00462397,0.005501907,0.7396632],"study_design_scores_gemma":[0.0000133404,0.00004018307,0.0006619325,0.00001208145,0.00003410946,0.00006531586,0.00003663374,0.9818203,0.01296146,0.002837361,0.001502696,0.00001449443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09272228,0.0008261654,0.8962312,0.0003379258,0.00009327677,0.00008307268,0.0004282813,0.005646036,0.003631803],"genre_scores_gemma":[0.707249,0.0004588575,0.2823955,0.0002835551,0.00009372743,0.0001050551,0.002174763,0.0002238592,0.007015651],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008486856,"threshold_uncertainty_score":0.01687491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02069469471490433,"score_gpt":0.2575391312440205,"score_spread":0.2368444365291162,"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."}}