{"id":"W4256023664","doi":"10.32920/ryerson.14654901","title":"An Intelligent Aircraft Window System for Visual Comfort Control","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Impact of Light on Environment and Health","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Illuminance; Computer science; Window (computing); Daylight; Transparency (behavior); Control system; Simulation; Computer vision; Artificial intelligence; Real-time computing; Engineering; Electrical engineering; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008361153,0.000448028,0.0006649558,0.00005145451,0.0002255943,0.0001597397,0.0005398752,0.0004055581,0.003502084],"category_scores_gemma":[0.0000131758,0.0003971494,0.0002872879,0.00005855734,0.0001356686,0.0002069678,0.0004382063,0.000419145,0.0002711769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00121996,"about_ca_system_score_gemma":0.00008609887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007893579,"about_ca_topic_score_gemma":0.0002753921,"domain_scores_codex":[0.9970124,0.000128391,0.0006133202,0.0008616775,0.0005861198,0.0007980756],"domain_scores_gemma":[0.9983993,0.0000777797,0.0002485038,0.0007143088,0.00000928218,0.0005508547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001530286,0.005795422,0.8366662,0.003562934,0.0008956987,0.0001756065,0.0049971,0.0561029,0.02362564,0.001948328,0.008480802,0.05621905],"study_design_scores_gemma":[0.007639993,0.004004358,0.739279,0.0009132604,0.000947687,0.00009980531,0.008988042,0.1340533,0.05181485,0.0006366771,0.04604476,0.005578276],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8204041,0.0001146338,0.1651012,0.0006715666,0.001296177,0.002764832,0.00007945233,0.0002777538,0.009290346],"genre_scores_gemma":[0.9929802,0.00004077676,0.004021411,0.000978063,0.0002926509,0.000220093,0.0002525971,0.00006117562,0.001153005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1725761,"threshold_uncertainty_score":0.9998481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01756726232530623,"score_gpt":0.2932934307599367,"score_spread":0.2757261684346304,"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."}}