{"id":"W2899064365","doi":"10.1080/19401493.2018.1536167","title":"The impact of local variations in a temperate maritime climate on building energy use","year":2018,"lang":"en","type":"article","venue":"Journal of Building Performance Simulation","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Engineering and Physical Sciences Research Council","keywords":"Environmental science; Microclimate; Meteorology; Temperate climate; Climatology; Climate zones; Building energy simulation; Atmospheric sciences; Energy (signal processing); Geography; Physical geography; Energy performance; Statistics; Mathematics; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004229382,0.000131231,0.0001801222,0.0002955114,0.0001672542,0.000065509,0.0001400393,0.00008657389,0.00000965699],"category_scores_gemma":[0.00004371029,0.00009714377,0.00009313824,0.0004138416,0.00004845863,0.0006686059,0.00001897939,0.0001806419,4.029714e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002143324,"about_ca_system_score_gemma":0.00003480515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003352263,"about_ca_topic_score_gemma":0.0000110915,"domain_scores_codex":[0.9988974,0.0000361913,0.0005618391,0.00007737368,0.0002024502,0.0002247713],"domain_scores_gemma":[0.9991646,0.0002093811,0.0002361721,0.0001434889,0.0002052394,0.00004115015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001311064,0.0000221876,0.009637847,0.000009052339,0.00003689271,6.560184e-7,0.00007048246,0.9774306,0.001822982,0.001075091,0.00001748609,0.009745661],"study_design_scores_gemma":[0.0003935197,0.0002370864,0.03006423,0.0001862981,0.00001136556,0.000007975929,0.000006795358,0.9642106,0.004547338,0.0001226264,0.0001143289,0.00009787349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8233141,0.0000359001,0.1762814,0.00000851071,0.0002521846,0.00003222879,0.000001812647,0.00002181551,0.00005209337],"genre_scores_gemma":[0.9973098,0.0002692092,0.002193513,0.000009836924,0.0001827501,0.000001814142,0.000002015484,0.00002321234,0.000007832196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1740879,"threshold_uncertainty_score":0.3961408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01074882741089144,"score_gpt":0.2594513727523387,"score_spread":0.2487025453414473,"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."}}