{"id":"W1987943629","doi":"10.1080/01431161.2014.902549","title":"Synoptic mapping of high-rise buildings in urban areas based on combined shadow analysis and scale space processing","year":2014,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Beijing; Shadow (psychology); Remote sensing; Satellite imagery; Pixel; Scale (ratio); Computer science; Satellite; Geography; Artificial intelligence; Cartography; China; Engineering","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":[0.0001783837,0.0003116009,0.0002046573,0.001905068,0.0001824602,0.0004920608,0.0002283584,0.0001327255,0.001293329],"category_scores_gemma":[0.000165869,0.0002202308,0.000179479,0.001050092,0.0001931423,0.0004829528,0.0004246671,0.0001378404,0.000230565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001628083,"about_ca_system_score_gemma":0.0003133382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002980423,"about_ca_topic_score_gemma":0.009130933,"domain_scores_codex":[0.9998872,0.00001385454,0.000005530087,0.00002497301,0.0000543114,0.00001407929],"domain_scores_gemma":[0.999885,0.00001991361,0.00002507278,0.00001612252,0.00004094411,0.0000128978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002469278,0.0001779493,0.04921785,0.000492349,0.0001333423,0.0002775747,0.0005045107,0.05063102,0.2608885,0.002337009,0.00275711,0.6323358],"study_design_scores_gemma":[0.00007798077,0.0003725649,0.4218152,0.00005608945,0.0001169895,0.0006713339,0.0007862035,0.5245093,0.0360944,0.003458911,0.01194438,0.00009666318],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5891274,0.0005895772,0.3980821,0.00009209066,0.00003574213,0.0002650485,0.001870297,0.002293199,0.007644591],"genre_scores_gemma":[0.7384393,0.000291073,0.257845,0.00001818472,0.00003256588,0.0001149312,0.001398578,0.00009220898,0.001768199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002980423,"threshold_uncertainty_score":0.005926132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006847545527310313,"score_gpt":0.2100057511686915,"score_spread":0.2031582056413812,"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."}}