{"id":"W3156804984","doi":"10.1111/mice.12698","title":"Similarity learning to enable building searches in post‐event image data","year":2021,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Research Foundation of Korea","keywords":"Metadata; Similarity (geometry); Rank (graph theory); Convolutional neural network; Computer science; Event (particle physics); Image (mathematics); Information retrieval; Global Positioning System; Data mining; Artificial intelligence; World Wide Web; Mathematics","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":[0.0007550195,0.0004554552,0.0007187,0.00231681,0.00044644,0.001036772,0.001325559,0.00108748,0.003537389],"category_scores_gemma":[0.002986366,0.0002631761,0.0007894657,0.002225381,0.0003661207,0.001923182,0.001479798,0.0008099789,0.002449331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004735558,"about_ca_system_score_gemma":0.0007490741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004397141,"about_ca_topic_score_gemma":0.007290261,"domain_scores_codex":[0.999374,0.00007618687,0.00004326928,0.0001843581,0.0002365817,0.00008565657],"domain_scores_gemma":[0.9990195,0.0002472146,0.0001042192,0.0002569552,0.0003154496,0.00005666275],"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":[0.0004441142,0.0008202099,0.00946711,0.0001892222,0.0001627329,0.0001767933,0.0001959556,0.0602199,0.05702017,0.007061318,0.01477432,0.8494681],"study_design_scores_gemma":[0.00001905195,0.00009955638,0.003360823,0.00001003716,0.00002663044,0.0001290481,0.00009542912,0.968304,0.01865824,0.005245448,0.004035188,0.00001648019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09971588,0.0003521848,0.8872883,0.0001982867,0.000128476,0.000175257,0.001257046,0.007481255,0.003403291],"genre_scores_gemma":[0.6001863,0.0001906933,0.3911768,0.0001345293,0.0001035287,0.000122178,0.004530171,0.0003035746,0.003252304],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004397141,"threshold_uncertainty_score":0.01183373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0115990024269123,"score_gpt":0.2272478540591881,"score_spread":0.2156488516322758,"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."}}