{"id":"W2900784907","doi":"10.1049/iet-wss.2018.5032","title":"Hybrid user action prediction system for automated home using association rules and ontology","year":2018,"lang":"en","type":"article","venue":"IET Wireless Sensor Systems","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Ontology; Computer science; Home automation; The Internet; Automation; Graph; Internet of Things; Artificial intelligence; Machine learning; World Wide Web; Theoretical computer science; Telecommunications; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009254923,0.0002764155,0.0005691152,0.0002699858,0.0004360446,0.0005209171,0.0002724775,0.0002684229,0.000001337232],"category_scores_gemma":[0.00007790954,0.000285036,0.00009781649,0.0002229383,0.00005223154,0.00105921,0.00008001835,0.0001270746,0.00006142008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009324616,"about_ca_system_score_gemma":0.00008747564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006796145,"about_ca_topic_score_gemma":0.00008592317,"domain_scores_codex":[0.9971846,0.0005277001,0.0006607659,0.0007014543,0.0004443883,0.0004810742],"domain_scores_gemma":[0.9973993,0.0004371961,0.0007614345,0.0004626837,0.0008069707,0.0001324142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001120674,0.001211457,0.1697266,0.01327953,0.004821207,0.0002491186,0.0132346,0.002237084,0.6396213,0.03103962,0.0360368,0.08742199],"study_design_scores_gemma":[0.001081255,0.0001868709,0.003626366,0.0003918241,0.00005753164,0.0007893711,0.0004632306,0.9854487,0.004609714,0.0000166438,0.00297496,0.0003535243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6943175,0.00006946353,0.2968903,0.00007530725,0.005862087,0.0009244484,0.000138856,0.001615594,0.0001064968],"genre_scores_gemma":[0.9972382,0.000004963109,0.001209136,0.00002070321,0.001042128,0.0001319626,0.00002575043,0.00003679869,0.0002903215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9832116,"threshold_uncertainty_score":0.9999602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0380131483343573,"score_gpt":0.2785626743064144,"score_spread":0.2405495259720571,"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."}}