{"id":"W4404472223","doi":"10.1117/12.3033670","title":"Measurements of atmospheric background light in the urban area Waterloo and its impact on satellite QKD system performance","year":2024,"lang":"en","type":"article","venue":"","topic":"Impact of Light on Environment and Health","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Research Council Canada; Bundesministerium für Bildung und Forschung","keywords":"Satellite; Remote sensing; Computer science; Communications satellite; Telecommunications; Atmospheric model; Environmental science; Meteorology; Geography; Engineering; Aerospace 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008153668,0.0001826886,0.0001747746,0.00001559511,0.00007540212,0.00005170191,0.0001902822,0.00005504561,0.0006485109],"category_scores_gemma":[0.000002122577,0.00009389285,0.00004805461,0.0002117014,0.00004575762,0.0002924014,0.00004785813,0.0001322428,0.0004455493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004021383,"about_ca_system_score_gemma":0.00001032147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000223999,"about_ca_topic_score_gemma":0.00003600833,"domain_scores_codex":[0.9985302,0.00007721987,0.0002638663,0.0002542797,0.0004972249,0.0003772057],"domain_scores_gemma":[0.9996209,0.00003643193,0.00003801951,0.0002061029,0.000001866102,0.00009671162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008320267,0.0001484814,0.9834292,0.0002960891,0.00002930832,0.00001329469,0.004128142,0.0002969758,0.00606648,0.0001030703,0.000634637,0.004771097],"study_design_scores_gemma":[0.0002434459,0.0004870768,0.9882261,0.000183633,0.00001608642,0.00001482068,0.0003830269,0.004064357,0.004654995,0.000004778964,0.001556809,0.0001648551],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9699776,0.0006738622,0.000002699663,0.0003068585,0.00008360564,0.0003077018,0.000002040507,0.00002670847,0.02861891],"genre_scores_gemma":[0.9984952,0.0002078202,0.00004732022,0.0001255939,0.00002679787,0.000009752457,0.000002547611,0.00001390799,0.001071024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02851762,"threshold_uncertainty_score":0.7100739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03082500145549923,"score_gpt":0.2592812232203446,"score_spread":0.2284562217648454,"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."}}