{"id":"W2775800479","doi":"10.1109/igarss.2017.8127388","title":"Impervious surface area extraction using simulated EnMAP imagery","year":2017,"lang":"en","type":"article","venue":"","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Impervious surface; Hyperspectral imaging; Endmember; Remote sensing; Environmental science; Albedo (alchemy); Image resolution; Scale (ratio); Multispectral image; Computer science; Geology; Geography; Cartography; Artificial intelligence","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":[0.0002367646,0.000497998,0.0001749339,0.0004619475,0.0001529565,0.0003229524,0.0002829554,0.0004206462,0.000934109],"category_scores_gemma":[0.0004167544,0.0001664739,0.0004914986,0.0004907776,0.0001790937,0.0003984857,0.0001801238,0.0002522062,0.0002410886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002592042,"about_ca_system_score_gemma":0.0002381617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01030507,"about_ca_topic_score_gemma":0.009692243,"domain_scores_codex":[0.9999287,0.00001687045,0.000002983797,0.00001754058,0.00001853503,0.00001536658],"domain_scores_gemma":[0.9998901,0.00003677386,0.00001090523,0.0000159794,0.00003848627,0.000007774709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001356108,0.0001195595,0.01136108,0.00007529021,0.00004767338,0.0001569515,0.00008129322,0.9469103,0.0101869,0.0006949046,0.001240888,0.02898957],"study_design_scores_gemma":[0.000007632558,0.00001006572,0.003662198,0.000002976886,0.000004273547,0.00001141024,0.00002146889,0.994032,0.001673774,0.000220528,0.0003472744,0.000006556612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.949719,0.00008953234,0.04304207,0.00009983483,0.00002842174,0.00005040052,0.001783164,0.0006596386,0.004528011],"genre_scores_gemma":[0.9686564,0.00004786154,0.02921784,0.00001626562,0.000005126175,0.00002868743,0.001434618,0.00004193587,0.0005512225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01030507,"threshold_uncertainty_score":0.02049017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0350415718318746,"score_gpt":0.287298033170177,"score_spread":0.2522564613383024,"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."}}