{"id":"W4414033870","doi":"10.1007/s10618-025-01158-8","title":"Detecting and reacting to smart home novelties","year":2025,"lang":"en","type":"article","venue":"Data Mining and Knowledge Discovery","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Network for Business Sustainability","funders":"Defense Advanced Research Projects Agency; National Institutes of Health; National Science Foundation","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007028707,0.0001778046,0.000218956,0.0002611027,0.0002471804,0.0008688878,0.001162335,0.0000578654,4.141527e-7],"category_scores_gemma":[0.0006594614,0.000172417,0.00001435404,0.000429698,0.00006290326,0.002038634,0.004953078,0.0001199344,0.000004579254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002211081,"about_ca_system_score_gemma":0.00009204408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001320205,"about_ca_topic_score_gemma":0.0001919834,"domain_scores_codex":[0.9985772,0.00004767171,0.0002295491,0.0007730906,0.00008960863,0.0002829012],"domain_scores_gemma":[0.9980706,0.000463424,0.00006175001,0.001290758,0.00003621024,0.00007724136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001500844,0.00005198387,0.01799797,0.000125701,0.00004589805,0.00001178833,0.003366373,1.464531e-7,0.001668309,0.005453178,0.01609216,0.9551715],"study_design_scores_gemma":[0.006115146,0.002073359,0.191786,0.01670648,0.0006207894,0.000734457,0.03648766,0.1727416,0.06531206,0.01167699,0.4865113,0.009234156],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7623022,0.001533696,0.2255086,0.0004724055,0.0006716693,0.000200356,0.0002555908,0.0005662417,0.008489294],"genre_scores_gemma":[0.846014,0.0000594098,0.1524471,0.0002084791,0.00007219225,0.00001722127,0.00009320495,0.0000142947,0.001074042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9459373,"threshold_uncertainty_score":0.8378705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03636783725970738,"score_gpt":0.3125553640990832,"score_spread":0.2761875268393759,"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."}}