{"id":"W4226018817","doi":"10.3390/electronics11071143","title":"OntoDomus: A Semantic Model for Ambient Assisted Living System Based on Smart Homes","year":2022,"lang":"en","type":"article","venue":"Electronics","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"AGE-WELL","keywords":"Ontology; Ambient intelligence; Multidisciplinary approach; Computer science; Context (archaeology); Terminology; Protégé; Web Ontology Language; Process (computing); Rotation formalisms in three dimensions; Semantic Web; Assisted living; Home automation; Independent living; OWL-S; Ubiquitous computing; Human–computer interaction; Adaptation (eye); Reusability; Context awareness; World Wide Web; Psychology; Software; Social Semantic Web; Phone","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":[0.001086272,0.0002144233,0.0003252248,0.0002350162,0.0005406255,0.0001925625,0.0007833162,0.00004217944,0.000009807763],"category_scores_gemma":[0.00008152614,0.0002347257,0.0002086339,0.0004662716,0.00001230886,0.0002230553,0.0002245571,0.0003042571,0.00001925551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001287607,"about_ca_system_score_gemma":0.00058881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002557566,"about_ca_topic_score_gemma":0.0001741347,"domain_scores_codex":[0.997539,0.0002927186,0.0003341887,0.000610123,0.0006171715,0.0006068044],"domain_scores_gemma":[0.9982285,0.0006269855,0.000215333,0.0007230268,0.0001206234,0.00008549427],"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":[0.0008250789,0.006665431,0.001741359,0.002657834,0.001046757,0.0001974286,0.0095762,0.3285291,0.02264899,0.1086333,0.02707418,0.4904043],"study_design_scores_gemma":[0.0005315789,0.0004547752,0.0001018843,0.0000900264,0.00001756868,0.0000475809,0.00009372998,0.9927429,0.0003719448,0.0001135056,0.005165838,0.0002686996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01997714,0.0004923596,0.9763365,0.0006108205,0.0005478493,0.0008844167,0.00002521918,0.0005500464,0.0005756282],"genre_scores_gemma":[0.9956815,0.000002861086,0.002257508,0.0004703181,0.00004243928,0.0007404173,0.0000121223,0.00003246195,0.0007604249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9757043,"threshold_uncertainty_score":0.9571834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02597186916362702,"score_gpt":0.2446003682889282,"score_spread":0.2186284991253012,"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."}}