{"id":"W6906440923","doi":"10.17632/x8vvch2sw9","title":"Room-level data of Simulated Energy consumption and Ventilation dynamics (RSimEV)","year":2024,"lang":"en","type":"dataset","venue":"Mendeley Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Energy consumption; Building energy simulation; Set (abstract data type); Data set; Energy (signal processing); Ventilation (architecture); Ranging","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007463642,0.001051849,0.0007110206,0.001018718,0.0003329466,0.001123137,0.002197415,0.001425971,0.02614094],"category_scores_gemma":[0.003535082,0.0003860524,0.001201632,0.002114758,0.0002536819,0.0009214003,0.00079132,0.00117239,0.01624464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001060064,"about_ca_system_score_gemma":0.001176071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01763997,"about_ca_topic_score_gemma":0.02348782,"domain_scores_codex":[0.9994404,0.00008868874,0.00005643709,0.0001543188,0.0001806793,0.00007951971],"domain_scores_gemma":[0.9984987,0.0005084624,0.00008815106,0.0003592071,0.0004501944,0.0000952852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002947364,0.0001583766,0.01002976,0.0008479026,0.000110915,0.00009474145,0.00007598226,0.04967265,0.0009490699,0.002103423,0.921786,0.01387658],"study_design_scores_gemma":[0.0005940959,0.0001777364,0.02615537,0.0004509999,0.00007651843,0.0001963591,0.0003535787,0.08668272,0.005336409,0.0052757,0.87454,0.0001604196],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004105886,0.00005692643,0.001123444,0.0001323121,0.00007263711,0.00003340735,0.9906281,0.001884489,0.001962858],"genre_scores_gemma":[0.01271127,0.00005699776,0.00222573,0.00007264924,0.00001475862,0.0001485239,0.9835389,0.0002609089,0.0009702759],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02614094,"threshold_uncertainty_score":0.08745021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1773565963024448,"score_gpt":0.3644538831227805,"score_spread":0.1870972868203357,"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."}}