{"id":"W4385076727","doi":"10.1016/j.buildenv.2023.110651","title":"Unsupervised domain adaptation with and without access to source data for estimating occupancy and recognizing activities in smart buildings","year":2023,"lang":"en","type":"article","venue":"Building and Environment","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Occupancy; Domain adaptation; Adaptation (eye); Computer science; Domain (mathematical analysis); Real-time computing; Environmental science; Data mining; Artificial intelligence; Engineering; Architectural engineering; Mathematics; Psychology","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":[0.000465661,0.0004714502,0.0006625544,0.0005001558,0.0001899639,0.0004467384,0.0007912121,0.0004922417,0.000553655],"category_scores_gemma":[0.001278173,0.0002176596,0.0005789834,0.0007133578,0.0003373327,0.0007491437,0.0007912393,0.0007315309,0.000530192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000180209,"about_ca_system_score_gemma":0.0004840202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005375487,"about_ca_topic_score_gemma":0.007768321,"domain_scores_codex":[0.9996417,0.0001042987,0.00001711237,0.0001190905,0.00005460205,0.00006320143],"domain_scores_gemma":[0.9995389,0.0002172897,0.00002981595,0.00009662919,0.00009315206,0.00002422591],"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":[0.0006119465,0.0007568341,0.009779428,0.0001151663,0.0001970569,0.0001554353,0.0002173927,0.2668016,0.04726193,0.001327352,0.003650789,0.6691251],"study_design_scores_gemma":[0.000009953147,0.00003441187,0.003782723,0.000004162398,0.00001827772,0.00003637999,0.00005119781,0.9894798,0.005338907,0.0007600816,0.0004732111,0.00001094835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2800055,0.0006614515,0.7148505,0.0001094555,0.0001150703,0.00005287939,0.0004202727,0.00185194,0.001932901],"genre_scores_gemma":[0.8954211,0.0002346555,0.1010735,0.00008171591,0.00005955979,0.00006816292,0.001278541,0.00009941245,0.001683227],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005375487,"threshold_uncertainty_score":0.01068836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08416189069732156,"score_gpt":0.2963959288487572,"score_spread":0.2122340381514357,"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."}}