{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00101803,0.0001934474,0.0002884857,0.0003185468,0.0002733764,0.0003372153,0.0004208926,0.00009341165,0.000001309396],"category_scores_gemma":[0.0002363682,0.0002022107,0.00002909251,0.0005146537,0.00005508943,0.001712556,0.0005289929,0.0001017124,0.000001249298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002905804,"about_ca_system_score_gemma":0.00004750301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005958477,"about_ca_topic_score_gemma":0.000322563,"domain_scores_codex":[0.9983759,0.00009221632,0.0002960049,0.0007098555,0.0001843147,0.0003417313],"domain_scores_gemma":[0.9986069,0.0007319573,0.00014961,0.0003812368,0.00004654456,0.00008374427],"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":[0.00005803357,0.00003517284,0.01170567,0.0001543649,0.0000451398,0.00000907879,0.004974876,0.000157379,0.008015673,0.004358579,0.0004173244,0.9700687],"study_design_scores_gemma":[0.001744145,0.0001061773,0.002244566,0.0005255761,0.00001812804,0.0000665451,0.001857451,0.9564714,0.002089435,0.006861249,0.02741254,0.0006027432],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4309488,0.0001029305,0.5680361,0.0003547117,0.0001780165,0.0001242474,0.00001348861,0.0001907057,0.0000510506],"genre_scores_gemma":[0.8518652,0.00003784864,0.1475233,0.0001609996,0.000109718,0.00007337843,0.00004608586,0.00002180417,0.0001616356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.969466,"threshold_uncertainty_score":0.8245913,"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."}}