{"id":"W4390665874","doi":"10.9734/bpi/mono/978-81-969208-6-9/ch2","title":"An Elite Roadway Illuminance Calculation (ERIC) Method Provides Optimum Performance and Cost-saving without Compromising Safety","year":2024,"lang":"en","type":"book-chapter","venue":"","topic":"Impact of Light on Environment and Health","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Eli Lilly (Canada)","funders":"","keywords":"Illuminance; Luminance; Government (linguistics); Sample (material); Architectural engineering; Usability; Engineering; Computer science; Operations research; Transport engineering; Artificial intelligence; Human–computer interaction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001078931,0.0006350913,0.000500978,0.001216278,0.0005626793,0.002122792,0.001342152,0.0005627917,0.01959828],"category_scores_gemma":[0.002043032,0.0002681283,0.0005493585,0.001083363,0.0006911726,0.001896606,0.001016403,0.0008187964,0.007741052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001168191,"about_ca_system_score_gemma":0.001179741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002460678,"about_ca_topic_score_gemma":0.004647509,"domain_scores_codex":[0.998806,0.0002161339,0.00004099196,0.0001726178,0.0007032464,0.00006104576],"domain_scores_gemma":[0.9990593,0.0002891982,0.00005590047,0.0001426808,0.0004153526,0.00003763467],"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":[0.0001451488,0.0001232817,0.002699003,0.0008756449,0.00002820479,0.00009391829,0.0006937323,0.01101831,0.0199128,0.06537957,0.0369285,0.8621019],"study_design_scores_gemma":[0.00008243128,0.0008167082,0.01183496,0.0005957003,0.0001303079,0.001450567,0.001373997,0.04953194,0.05680797,0.02855127,0.8486063,0.0002178307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01930382,0.002300726,0.6296655,0.0006880901,0.0005571011,0.0003807315,0.0002487375,0.003889248,0.342966],"genre_scores_gemma":[0.2789758,0.003478882,0.4543861,0.0005322843,0.0002230497,0.0004176653,0.0003982233,0.002183694,0.2594045],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01959828,"threshold_uncertainty_score":0.06556278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0220209484916296,"score_gpt":0.2813149486882152,"score_spread":0.2592940001965856,"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."}}