{"id":"W187587118","doi":"10.1007/978-3-642-21535-3_5","title":"Activity Recognition in Smart Environments: An Information Retrieval Problem","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Activity recognition; Computer science; Activities of daily living; Smart environment; Process (computing); Artificial intelligence; Machine learning; Home automation; Human–computer interaction; Internet of Things; World Wide Web","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":[0.001954587,0.001043369,0.003913955,0.003760396,0.001052385,0.004046161,0.00301598,0.004148944,0.003202494],"category_scores_gemma":[0.008353255,0.0008746281,0.002001496,0.007011623,0.001339538,0.007743843,0.001950912,0.001861074,0.002717725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001011139,"about_ca_system_score_gemma":0.001051446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008191648,"about_ca_topic_score_gemma":0.005894334,"domain_scores_codex":[0.9976495,0.0004217528,0.000289369,0.00082168,0.0006415728,0.0001761301],"domain_scores_gemma":[0.9963833,0.002437489,0.00028776,0.0003776688,0.0004328082,0.00008091503],"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":[0.0002652915,0.0004345778,0.003214401,0.001029048,0.0001819344,0.0004785914,0.0005000271,0.040525,0.00508211,0.01808934,0.02657927,0.9036204],"study_design_scores_gemma":[0.0001559063,0.000323032,0.005610976,0.0002697528,0.0003538248,0.002125682,0.001735371,0.7702864,0.01054361,0.183645,0.02475492,0.0001956212],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.03192997,0.01260968,0.9427823,0.003513552,0.0002486758,0.0002408075,0.001600401,0.001581699,0.005492954],"genre_scores_gemma":[0.4272833,0.0194971,0.5270782,0.001492213,0.002072377,0.0005707198,0.00608832,0.0004094703,0.01550838],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.008191648,"threshold_uncertainty_score":0.01628792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03323290163610457,"score_gpt":0.2335718302412678,"score_spread":0.2003389286051633,"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."}}