{"id":"W2821046059","doi":"10.1371/journal.pone.0199545","title":"Bright lights, big city: Causal effects of population and GDP on urban brightness","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Impact of Light on Environment and Health","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Population; Brightness; Geography; Environmental science; Environmental health; Medicine; Physics; Astronomy","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001480513,0.0001344196,0.0002177799,0.00003751364,0.0001490916,0.00001349168,0.00009720328,0.00007957571,0.0004858166],"category_scores_gemma":[0.00002804387,0.000109476,0.00002213189,0.0001036513,0.0002095106,0.0001302955,0.0000672191,0.00008829839,0.0002365672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001111864,"about_ca_system_score_gemma":0.000004162161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000627411,"about_ca_topic_score_gemma":0.0001325475,"domain_scores_codex":[0.9987731,0.0000501626,0.0001835564,0.0002557352,0.0004470586,0.0002903706],"domain_scores_gemma":[0.9994338,0.0000628565,0.0001070595,0.0002319867,0.00000405125,0.0001602512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007595432,0.001233041,0.9392196,0.0001167989,0.00004096543,0.000004454875,0.0007109873,3.999293e-7,0.05581471,0.0002301616,0.0006851457,0.001867802],"study_design_scores_gemma":[0.0003621225,0.0004470257,0.8369847,0.00009551693,0.00004093981,6.84386e-7,0.000002305645,0.00003047626,0.1609752,0.0003410039,0.0005962708,0.0001237626],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954716,0.00003460279,0.00001403599,0.0004069714,0.00009783783,0.0002939368,0.000004139998,0.00002737912,0.003649509],"genre_scores_gemma":[0.9974232,0.00004276454,0.0002642631,0.0002904633,0.0002921479,0.000005990518,0.000009286811,0.00001555856,0.001656373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1051605,"threshold_uncertainty_score":0.5319351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02607555169506947,"score_gpt":0.2231615356662943,"score_spread":0.1970859839712248,"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."}}