{"id":"W4225264643","doi":"10.4018/978-1-6684-5295-0.ch026","title":"Comprehensive Ontological Model for Senior Wellness Activity Recognition in Smart Homes","year":2022,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Ontology; Activity recognition; Context (archaeology); Home automation; Identification (biology); Inference; Set (abstract data type); Computer science; Field (mathematics); Human–computer interaction; Smart objects; Smart environment; Artificial intelligence; Internet privacy; Internet of Things; Geography; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001210331,0.0006142972,0.0005555281,0.002224996,0.0009760597,0.003116583,0.001559621,0.001240734,0.002840698],"category_scores_gemma":[0.001921932,0.0004417535,0.001575606,0.002695779,0.0008335059,0.005052996,0.001860572,0.001541144,0.001379104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002025784,"about_ca_system_score_gemma":0.002669532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01582366,"about_ca_topic_score_gemma":0.01991734,"domain_scores_codex":[0.9988548,0.0002486513,0.0001796598,0.000230525,0.0003835335,0.0001028539],"domain_scores_gemma":[0.9993218,0.0002598094,0.00006233529,0.0001271715,0.000167021,0.00006184323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001062027,0.0003750359,0.005977688,0.0008452959,0.0001383744,0.001379539,0.004025475,0.03303485,0.007547215,0.6952662,0.02190673,0.2293973],"study_design_scores_gemma":[0.00002785623,0.00007816497,0.005817704,0.0009953781,0.0002551289,0.001327186,0.002462358,0.2707031,0.004851625,0.3588367,0.3545183,0.0001266041],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02262103,0.001890379,0.9293163,0.002200678,0.0002329763,0.0005320185,0.005304849,0.001724448,0.03617736],"genre_scores_gemma":[0.2135482,0.003372852,0.7528583,0.000818415,0.000104912,0.0008294778,0.01268604,0.0002463104,0.01553563],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01582366,"threshold_uncertainty_score":0.03146315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0747340704604796,"score_gpt":0.2826177264431696,"score_spread":0.20788365598269,"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."}}