{"id":"W4402031274","doi":"10.32920/26871310.v1","title":"Monitoring of a Productive Blue-Green Roof Using Low-Cost Sensors","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Roof; Green roof; Environmental science; Business; Remote sensing; Architectural engineering; Engineering; Civil engineering; Geography","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":[0.0001041054,0.0002128301,0.0001796826,0.0003464677,0.0001926609,0.0003710595,0.0002473835,0.000255722,0.00150543],"category_scores_gemma":[0.0001045938,0.0001147344,0.0001261756,0.0003090762,0.0001043028,0.0003013027,0.0001921099,0.0001221247,0.000368762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001837173,"about_ca_system_score_gemma":0.0001263211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002059259,"about_ca_topic_score_gemma":0.005488681,"domain_scores_codex":[0.9998635,0.00001317452,0.000002648413,0.00003360557,0.00006070704,0.00002645531],"domain_scores_gemma":[0.9999192,0.00001304645,0.00001541828,0.00001255254,0.00003073956,0.000009041594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002773211,0.0001548256,0.0414529,0.0001074093,0.00003704159,0.000259862,0.0001486741,0.0111673,0.8586236,0.0002902462,0.001681906,0.08579901],"study_design_scores_gemma":[0.0000360865,0.0004821471,0.4165325,0.00004081539,0.00007602837,0.0003797324,0.0008532727,0.1633203,0.4098024,0.0005803266,0.007850396,0.00004613843],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9414787,0.0001635502,0.05009885,0.00006124822,0.00002364994,0.00004511158,0.000785408,0.0006916008,0.006651771],"genre_scores_gemma":[0.9760476,0.0001069119,0.02188224,0.00002374165,0.000007158319,0.0000192485,0.0002557743,0.00002698022,0.001630333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002059259,"threshold_uncertainty_score":0.005036175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.020152573248056,"score_gpt":0.2448005086339635,"score_spread":0.2246479353859075,"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."}}