{"id":"W4389220681","doi":"10.1016/j.enbuild.2023.113808","title":"Unsupervised domain adaptation without source data for estimating occupancy and recognizing activities in smart buildings","year":2023,"lang":"en","type":"article","venue":"Energy and Buildings","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Transfer of learning; Classifier (UML); Artificial intelligence; Domain (mathematical analysis); Machine learning; Domain adaptation; Data mining","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002986942,0.0004878341,0.0006902313,0.0004851354,0.0001604203,0.0003822839,0.0007584546,0.0004494817,0.0005529181],"category_scores_gemma":[0.0009956615,0.0002311855,0.0005700752,0.0007210888,0.0002883391,0.0005941438,0.0006056103,0.0007122349,0.0005450753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001770322,"about_ca_system_score_gemma":0.0004159572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005206964,"about_ca_topic_score_gemma":0.007563316,"domain_scores_codex":[0.9997341,0.0000672929,0.00001153865,0.00009312175,0.00004613194,0.00004779788],"domain_scores_gemma":[0.9996842,0.0001480035,0.00002415597,0.00006681666,0.00005957704,0.00001717457],"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":[0.0004815563,0.0006661521,0.01011935,0.0001367036,0.0001658173,0.0001596778,0.0001508426,0.3507666,0.04148694,0.001551675,0.003872681,0.5904419],"study_design_scores_gemma":[0.00000670192,0.00002621854,0.003181884,0.000004258688,0.00001273624,0.00003009464,0.00003040569,0.9910378,0.004444253,0.0007957408,0.0004215945,0.000008321352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2355467,0.0006611997,0.7592251,0.00009283341,0.0001087479,0.00004738597,0.0005148093,0.001880897,0.001922317],"genre_scores_gemma":[0.9088898,0.0002460336,0.08755636,0.00006985946,0.00005917964,0.00006395276,0.001260144,0.00009033074,0.001764225],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005206964,"threshold_uncertainty_score":0.01035333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06053509487585384,"score_gpt":0.2834053101831179,"score_spread":0.2228702153072641,"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."}}