{"id":"W2900716661","doi":"10.1016/j.enbuild.2018.11.009","title":"An integrated model for position-based productivity and energy costs optimization in offices","year":2018,"lang":"en","type":"article","venue":"Energy and Buildings","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Productivity; Flexibility (engineering); Indoor air quality; Thermal comfort; Occupancy; Position (finance); Energy consumption; Architectural engineering; Energy (signal processing); Computer science; Simulation; Environmental economics; Environmental science; Engineering; Business; Environmental engineering; Meteorology; Mathematics; Geography; Economics","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":[0.0009410699,0.001060196,0.002528223,0.0007025111,0.0009042145,0.002625175,0.002658803,0.003815065,0.007763709],"category_scores_gemma":[0.002262078,0.001339215,0.001728386,0.00163092,0.0009613223,0.001504168,0.00141104,0.002015493,0.0008499066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002406138,"about_ca_system_score_gemma":0.002858019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05573148,"about_ca_topic_score_gemma":0.02900108,"domain_scores_codex":[0.9993966,0.0001663812,0.00002410156,0.0001135159,0.0001153714,0.0001841354],"domain_scores_gemma":[0.9992467,0.0004435946,0.00005525109,0.00003886017,0.0001295642,0.00008601319],"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":[0.000008775536,0.00001244748,0.00007094298,0.000005353033,0.000003406747,0.000009309831,0.00000422345,0.9982893,0.00004424882,0.0008802762,0.00008674544,0.0005848929],"study_design_scores_gemma":[0.000006656058,0.000005549234,0.00005829649,0.000002038105,0.000003414568,0.000001885119,0.000004434795,0.999324,0.00003301699,0.0004309006,0.000127544,0.000002213359],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2150862,0.0009877061,0.723562,0.001179704,0.0002528972,0.000198222,0.001940423,0.000558301,0.0562346],"genre_scores_gemma":[0.949541,0.0004067589,0.02633456,0.0001107705,0.00006838256,0.0002918562,0.0006012998,0.0001627988,0.02248253],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05573148,"threshold_uncertainty_score":0.1108142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00579696512643671,"score_gpt":0.2034484086199939,"score_spread":0.1976514434935572,"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."}}