{"id":"W1521384697","doi":"","title":"Automatic Road Change Detection and GIS Updating from High Spatial Remotely-Sensed Imagery","year":2004,"lang":"en","type":"article","venue":"地球空间信息科学学报：英文版","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Conflation; Change detection; Computer science; Artificial intelligence; Matching (statistics); Geographic information system; Wavelet; Feature extraction; Data mining; Computer vision; Geography; Remote sensing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001023762,0.0002519763,0.000253279,0.0001501905,0.0001633236,0.0001001536,0.00008224848,0.0002016486,0.000102832],"category_scores_gemma":[0.00004683548,0.0002599803,0.00005774634,0.0002135998,0.00003401882,0.0004229468,0.00003363397,0.000275802,0.0001155967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001653283,"about_ca_system_score_gemma":0.00001150728,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007614816,"about_ca_topic_score_gemma":0.0006836272,"domain_scores_codex":[0.9988348,0.00002972193,0.0003108121,0.0002957494,0.0002044687,0.0003244728],"domain_scores_gemma":[0.9995088,0.00003841786,0.00008951018,0.0002397835,0.00002764899,0.0000958694],"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":[0.00001506357,0.00004016173,0.0002049658,0.0001244758,0.0000754816,0.00006189849,0.001975936,0.001672,0.2773912,0.00002056558,0.00008543528,0.7183328],"study_design_scores_gemma":[0.00239135,0.0001438536,0.41598,0.0005400705,0.0001726196,0.0001466324,0.0006839502,0.4160063,0.1608339,0.001044005,0.0009229082,0.001134417],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866558,0.0002479605,0.009410931,0.0001202538,0.001153579,0.0002290335,0.00001937716,0.001771053,0.0003919868],"genre_scores_gemma":[0.994956,0.0000701809,0.00404575,0.00005880294,0.000722547,0.0000204127,0.00004288103,0.0000688371,0.00001459997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7171984,"threshold_uncertainty_score":0.9999852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01019008469989637,"score_gpt":0.205079240630183,"score_spread":0.1948891559302866,"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."}}