{"id":"W2103379079","doi":"10.3390/rs3071380","title":"Geospatial Technologies to Improve Urban Energy Efficiency","year":2011,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Geospatial analysis; Urban heat island; Computer science; Environmental science; Efficient energy use; Remote sensing; Architectural engineering; Database; Meteorology; Geography; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.00109947,0.0008244154,0.000408803,0.002483883,0.0004910998,0.002544369,0.0009220875,0.0003724784,0.006698661],"category_scores_gemma":[0.002291653,0.0002351439,0.000422848,0.006319818,0.0004266725,0.001831283,0.001658304,0.0005597101,0.001510397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001452296,"about_ca_system_score_gemma":0.001594984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0653168,"about_ca_topic_score_gemma":0.08031167,"domain_scores_codex":[0.9991622,0.0002152071,0.00003141084,0.00007420243,0.0004458351,0.00007107879],"domain_scores_gemma":[0.9989831,0.0002050468,0.00005624968,0.0002507702,0.0004655055,0.00003932797],"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":[0.0001048195,0.0001644825,0.01267743,0.000413425,0.0001244196,0.00009449455,0.0007778631,0.04623711,0.01503919,0.07056139,0.06837712,0.7854282],"study_design_scores_gemma":[0.0001079989,0.0001393048,0.03854647,0.0003330307,0.0001769096,0.0002051123,0.003177009,0.1603608,0.03977907,0.06987228,0.6871479,0.0001542624],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08378761,0.006284071,0.7136211,0.00615205,0.0004523747,0.0003919899,0.01528621,0.02694225,0.1470823],"genre_scores_gemma":[0.4406836,0.00538073,0.5249904,0.0006031594,0.0001125359,0.0003073563,0.01205838,0.001863425,0.01400046],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0653168,"threshold_uncertainty_score":0.1298732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01054801625993265,"score_gpt":0.1910854219257153,"score_spread":0.1805374056657826,"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."}}