{"id":"W2135634960","doi":"","title":"Optimization od daylight in buildings to save energy and to improve visual comfort: analysis in different latitudes","year":2009,"lang":"en","type":"article","venue":"Research Padua  Archive (University of Padua)","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Daylight; GLARE; Daylighting; Shading; Architectural engineering; Radiance; Artificial light; Electric light; Light intensity; Sunlight; Luminance; Computer science; Software; Environmental science; Engineering; Illuminance; Computer graphics (images); Artificial intelligence; Geography; Remote sensing; Electrical engineering; Optics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001595109,0.0003083598,0.0003350452,0.000327153,0.0001856935,0.0005247191,0.0001407895,0.0001973599,0.001003434],"category_scores_gemma":[0.0002430305,0.0001303218,0.0004120908,0.0004518222,0.0001918708,0.0002044451,0.0001660988,0.000118044,0.0001480714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003575742,"about_ca_system_score_gemma":0.0001614463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004136114,"about_ca_topic_score_gemma":0.005759375,"domain_scores_codex":[0.9998865,0.00003850992,0.000003292102,0.00001328137,0.00003153831,0.00002672413],"domain_scores_gemma":[0.9999059,0.00005136712,0.00001365322,0.000005555076,0.00001607378,0.000007338312],"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":[0.0002399576,0.00008627813,0.008729632,0.000214044,0.00006533087,0.0001037183,0.0001033322,0.9278256,0.0279325,0.002190785,0.0004808932,0.03202788],"study_design_scores_gemma":[0.0000271604,0.000329627,0.04268437,0.00002073034,0.0000804012,0.00007512004,0.0002589163,0.9338952,0.01872661,0.0013466,0.002524826,0.00003044355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9299282,0.002296538,0.05416972,0.00004994073,0.00001566601,0.00002299142,0.0001499208,0.0001242781,0.01324288],"genre_scores_gemma":[0.9959252,0.0003499927,0.002840448,0.000006187593,0.000003101828,0.000006173924,0.00005062876,0.00002247546,0.0007959259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004136114,"threshold_uncertainty_score":0.00822407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01043908454785985,"score_gpt":0.2462595154508525,"score_spread":0.2358204309029927,"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."}}